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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,130 @@
+---
+library_name: transformers
+tags:
+- generated_from_trainer
+model-index:
+- name: lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.12.2`
+```yaml
+base_model: /lustre/fswork/projects/rech/qwv/udv55np/Gemma/base/gemma-3-4b
+
+datasets:
+- path: /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking
+  ds_type: json
+  type: chat_template
+  field_messages: conversations
+  data_files:
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0007.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0009.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0005.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0006.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0014.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0010.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0012.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0008.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0001.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0002.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0013.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0015.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0004.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0011.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0000.jsonl
+  - /lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0003.jsonl
+
+dataset_prepared_path: /lustre/fswork/projects/rech/dgo/udv55np/dataset_gemma/Nemotron-Super-49B-v1_5/split_0
+tokenizer_config: "/lustre/fswork/projects/rech/qwv/udv55np/Gemma/base/gemma-3-27b"
+chat_template: gemma3
+eot_tokens:
+  - "<end_of_turn>"
+
+shuffle_merged_datasets: true
+output_dir: /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0
+
+sequence_len: 16384
+sample_packing: true
+
+gradient_accumulation_steps: 1
+micro_batch_size: 1
+num_epochs: 0.6
+auto_resume_from_checkpoints: true
+
+optimizer: adamw_torch_fused
+lr_scheduler: warmup_stable_decay
+learning_rate: 5e-6
+lr_scheduler_kwargs:
+  num_decay_steps: 200
+  min_lr_ratio: 0.1
+warmup_steps: 100
+
+bf16: true
+tf32: false
+
+gradient_checkpointing: true
+logging_steps: 10
+flash_attention: true
+
+evals_per_epoch: 0
+saves_per_epoch: 1
+save_total_limit: 20
+save_only_model: true
+
+use_tensorboard: true
+deepspeed: /lustre/fswork/projects/rech/qwv/udv55np/axolotl/zero3.json
+
+```
+
+</details><br>
+
+# lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0
+
+This model was trained from scratch on the None dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 16
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: warmup_stable_decay
+- lr_scheduler_warmup_steps: 100
+- training_steps: 711
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.55.2
+- Pytorch 2.6.0+cu124
+- Datasets 4.0.0
+- Tokenizers 0.21.1

added_tokens.json

@@ -0,0 +1,3 @@
+{
+  "<image_soft_token>": 262144
+}

chat_template.jinja

@@ -0,0 +1,47 @@
+{{ bos_token }}
+{%- if messages[0]['role'] == 'system' -%}
+    {%- if messages[0]['content'] is string -%}
+        {%- set first_user_prefix = messages[0]['content'] + '
+
+' -%}
+    {%- else -%}
+        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
+
+' -%}
+    {%- endif -%}
+    {%- set loop_messages = messages[1:] -%}
+{%- else -%}
+    {%- set first_user_prefix = "" -%}
+    {%- set loop_messages = messages -%}
+{%- endif -%}
+{%- for message in loop_messages -%}
+    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
+        {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
+    {%- endif -%}
+    {%- if (message['role'] == 'assistant') -%}
+        {%- set role = "model" -%}
+    {%- else -%}
+        {%- set role = message['role'] -%}
+    {%- endif -%}
+    {{ '<start_of_turn>' + role + '
+' + (first_user_prefix if loop.first else "") }}
+    {%- if message['content'] is string -%}
+        {{ message['content'] | trim }}
+    {%- elif message['content'] is iterable -%}
+        {%- for item in message['content'] -%}
+            {%- if item['type'] == 'image' -%}
+                {{ '<start_of_image>' }}
+            {%- elif item['type'] == 'text' -%}
+                {{ item['text'] | trim }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{ raise_exception("Invalid content type") }}
+    {%- endif -%}
+    {{ '<end_of_turn>
+' }}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
+{%- endif -%}

config.json

@@ -0,0 +1,93 @@
+{
+  "architectures": [
+    "Gemma3ForConditionalGeneration"
+  ],
+  "boi_token_index": 255999,
+  "eoi_token_index": 256000,
+  "image_token_index": 262144,
+  "initializer_range": 0.02,
+  "mm_tokens_per_image": 256,
+  "model_type": "gemma3",
+  "text_config": {
+    "_sliding_window_pattern": 6,
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_logit_softcapping": null,
+    "final_logit_softcapping": null,
+    "head_dim": 256,
+    "hidden_activation": "gelu_pytorch_tanh",
+    "hidden_size": 2560,
+    "initializer_range": 0.02,
+    "intermediate_size": 10240,
+    "layer_types": [
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention"
+    ],
+    "max_position_embeddings": 131072,
+    "model_type": "gemma3_text",
+    "num_attention_heads": 8,
+    "num_hidden_layers": 34,
+    "num_key_value_heads": 4,
+    "query_pre_attn_scalar": 256,
+    "rms_norm_eps": 1e-06,
+    "rope_local_base_freq": 10000.0,
+    "rope_scaling": {
+      "factor": 8.0,
+      "rope_type": "linear"
+    },
+    "rope_theta": 1000000.0,
+    "sliding_window": 1024,
+    "torch_dtype": "bfloat16",
+    "use_cache": false,
+    "vocab_size": 262208
+  },
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.55.2",
+  "vision_config": {
+    "attention_dropout": 0.0,
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "image_size": 896,
+    "intermediate_size": 4304,
+    "layer_norm_eps": 1e-06,
+    "model_type": "siglip_vision_model",
+    "num_attention_heads": 16,
+    "num_channels": 3,
+    "num_hidden_layers": 27,
+    "patch_size": 14,
+    "torch_dtype": "bfloat16",
+    "vision_use_head": false
+  }
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "do_sample": true,
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "pad_token_id": 0,
+  "top_k": 64,
+  "top_p": 0.95,
+  "transformers_version": "4.55.2"
+}

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+}

preprocessor_config.json

@@ -0,0 +1,29 @@
+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_pan_and_scan": null,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "Gemma3ImageProcessor",
+  "image_seq_length": 256,
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
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+  "pan_and_scan_max_num_crops": null,
+  "pan_and_scan_min_crop_size": null,
+  "pan_and_scan_min_ratio_to_activate": null,
+  "processor_class": "Gemma3Processor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 896,
+    "width": 896
+  }
+}

processor_config.json

@@ -0,0 +1,4 @@
+{
+  "image_seq_length": 256,
+  "processor_class": "Gemma3Processor"
+}

runs/Nov24_00-10-02_jzxh298/events.out.tfevents.1763939502.jzxh298.1912876.0

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slurm.out

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+2: W1124 00:08:21.177000 270804 torch/distributed/run.py:792] 
+2: W1124 00:08:21.177000 270804 torch/distributed/run.py:792] *****************************************
+2: W1124 00:08:21.177000 270804 torch/distributed/run.py:792] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+2: W1124 00:08:21.177000 270804 torch/distributed/run.py:792] *****************************************
+3: W1124 00:08:21.180000 1900294 torch/distributed/run.py:792] 
+3: W1124 00:08:21.180000 1900294 torch/distributed/run.py:792] *****************************************
+3: W1124 00:08:21.180000 1900294 torch/distributed/run.py:792] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+3: W1124 00:08:21.180000 1900294 torch/distributed/run.py:792] *****************************************
+0: W1124 00:08:21.180000 1912798 torch/distributed/run.py:792] 
+0: W1124 00:08:21.180000 1912798 torch/distributed/run.py:792] *****************************************
+0: W1124 00:08:21.180000 1912798 torch/distributed/run.py:792] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+0: W1124 00:08:21.180000 1912798 torch/distributed/run.py:792] *****************************************
+1: W1124 00:08:21.306000 434889 torch/distributed/run.py:792] 
+1: W1124 00:08:21.306000 434889 torch/distributed/run.py:792] *****************************************
+1: W1124 00:08:21.306000 434889 torch/distributed/run.py:792] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+1: W1124 00:08:21.306000 434889 torch/distributed/run.py:792] *****************************************
+0: [2025-11-24 00:08:46,359] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:119] [PID:1912876] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
+0: [2025-11-24 00:08:46,359] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:218] [PID:1912876] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
+2: [2025-11-24 00:08:47,025] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:119] [PID:270879] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
+2: [2025-11-24 00:08:47,026] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:218] [PID:270879] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
+1: [2025-11-24 00:08:47,077] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:119] [PID:434964] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
+1: [2025-11-24 00:08:47,078] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:218] [PID:434964] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
+3: [2025-11-24 00:08:47,277] [INFO] [axolotl.utils.schemas.validation.check_eval_packing:119] [PID:1900370] [RANK:0] explicitly setting `eval_sample_packing` to match `sample_packing`
+3: [2025-11-24 00:08:47,277] [INFO] [axolotl.utils.schemas.validation.hint_sample_packing_padding:218] [PID:1900370] [RANK:0] Setting `pad_to_sequence_len: true` to prevent memory leaks when sample_packing
+0: [2025-11-24 00:08:49,792] [WARNING] [axolotl.utils.config.normalize_config:139] [PID:1912876] [RANK:0] Invalid value for save_steps (1.6666666666666667) from saves_per_epoch and/or num_epochs. Saving at training end only.
+0: [2025-11-24 00:08:49,874] [INFO] [axolotl.cli.config.load_cfg:245] [PID:1912876] [RANK:0] config:
+0: {
+0:   "activation_offloading": false,
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+0:   "axolotl_config_path": "/lustre/fswork/projects/rech/dgo/udv55np/train/tmp/1763939290239020138.yaml",
+0:   "base_model": "/lustre/fswork/projects/rech/qwv/udv55np/Gemma/base/gemma-3-4b",
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+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0009.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0005.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0006.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0014.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0010.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0012.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0008.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0001.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0002.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0013.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0015.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0004.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0011.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0000.jsonl",
+0:         "/lustre/fswork/projects/rech/qwv/udv55np/dataset/ift/Nemotron-Super-49B-v1_5/no_thinking/0003.jsonl"
+0:       ],
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+0:         "role": "role"
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+0:   "pad_to_sequence_len": true,
+0:   "pretrain_multipack_attn": true,
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+0:   "resources_per_worker": {
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+0:   "sample_packing": true,
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+0:   "save_only_model": true,
+0:   "save_safetensors": true,
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+0:   "tokenizer_config": "/lustre/fswork/projects/rech/qwv/udv55np/Gemma/base/gemma-3-27b",
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+0:     "use_vllm": false,
+0:     "vllm_server_host": "0.0.0.0",
+0:     "vllm_server_port": 8000
+0:   },
+0:   "use_ray": false,
+0:   "use_tensorboard": true,
+0:   "val_set_size": 0.0,
+0:   "vllm": {
+0:     "device": "auto",
+0:     "dtype": "auto",
+0:     "gpu_memory_utilization": 0.9,
+0:     "host": "0.0.0.0",
+0:     "port": 8000
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+0:   "warmup_steps": 100,
+0:   "weight_decay": 0.0,
+0:   "world_size": 16
+0: }
+0: [2025-11-24 00:08:49,876] [INFO] [axolotl.cli.checks.check_user_token:35] [PID:1912876] [RANK:0] Skipping HuggingFace token verification because HF_HUB_OFFLINE is set to True. Only local files will be used.
+0: [2025-11-24 00:08:51,148] [INFO] [axolotl.utils.data.shared.load_preprocessed_dataset:472] [PID:1912876] [RANK:0] Loading prepared dataset from disk at /lustre/fswork/projects/rech/dgo/udv55np/dataset_gemma/Nemotron-Super-49B-v1_5/split_0/06698e902d3dba325ca34849b1dea5ea...
+0: [2025-11-24 00:09:24,738] [INFO] [axolotl.utils.samplers.multipack.calc_min_len:436] [PID:1912876] [RANK:0] gather_len_batches: [18976, 18976, 18975, 18976, 18976, 18976, 18976, 18976, 18976, 18975, 18976, 18976, 18976, 18976, 18976, 18976]
+0: [2025-11-24 00:09:24,803] [INFO] [axolotl.utils.trainer.calc_sample_packing_eff_est:495] [PID:1912876] [RANK:0] sample_packing_eff_est across ranks: [0.9988827705383301, 0.9989354014396667, 0.9989354014396667, 0.9988827705383301, 0.9989354014396667, 0.9989354014396667, 0.9989354014396667, 0.9989354014396667, 0.9988827705383301, 0.9988827705383301, 0.9988827705383301, 0.9989880323410034, 0.9988301396369934, 0.9989354014396667, 0.9989354014396667, 0.9989354014396667]
+0: [2025-11-24 00:09:24,810] [INFO] [axolotl.utils.data.sft._prepare_standard_dataset:127] [PID:1912876] [RANK:0] Maximum number of steps set at 711
+1: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+1: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+1: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+1: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+2: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+3: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+0: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+0: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+2: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+0: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+3: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+2: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+3: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+3: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+2: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+0: Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
+0: [2025-11-24 00:09:31,797] [INFO] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_evaluation_loop:110] [PID:1912876] [RANK:0] Patched Trainer.evaluation_loop with nanmean loss calculation
+0: [2025-11-24 00:09:31,798] [INFO] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_maybe_log_save_evaluate:164] [PID:1912876] [RANK:0] Patched Trainer._maybe_log_save_evaluate with nanmean loss calculation
+0: 
+0: 
+1: 
+3: 
+2: 
+3: 
+3: 
+1: 
+1: 
+0: 
+1: 
+2: █| 2/2 [00:24<00:00, 12.34s/it]
+2: 
+2: 
+2: 
+3: 
+0: 
+0: [2025-11-24 00:09:59,406] [INFO] [axolotl.loaders.model._configure_embedding_dtypes:345] [PID:1912876] [RANK:0] Converting modules to torch.bfloat16
+0: [2025-11-24 00:10:03,242] [INFO] [axolotl.train.save_initial_configs:416] [PID:1912876] [RANK:0] Pre-saving tokenizer to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0...
+0: [2025-11-24 00:10:03,660] [INFO] [axolotl.train.save_initial_configs:419] [PID:1912876] [RANK:0] Pre-saving model config to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0...
+0: [2025-11-24 00:10:03,690] [INFO] [axolotl.train.save_initial_configs:423] [PID:1912876] [RANK:0] Pre-saving processor to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0...
+0: [2025-11-24 00:10:06,488] [INFO] [axolotl.train.execute_training:203] [PID:1912876] [RANK:0] Starting trainer...
+0: [2025-11-24 00:11:39,109] [INFO] [axolotl.utils.samplers.multipack.calc_min_len:436] [PID:1912876] [RANK:0] gather_len_batches: [18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976, 18976]
+0: Parameter Offload - Persistent parameters statistics: param_count = 479, numel = 768880
+0: {'loss': 0.7282, 'grad_norm': 2.3999579863224176, 'learning_rate': 9.05e-07, 'memory/max_mem_active(gib)': 57.15, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 66.2, 'epoch': 0.01}
+0: 
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+0: {'loss': 0.6672, 'grad_norm': 1.3408937334456381, 'learning_rate': 1.3550000000000002e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.02}
+0: {'loss': 0.6271, 'grad_norm': 0.8591296514459729, 'learning_rate': 1.805e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.03}
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+0: {'loss': 0.6047, 'grad_norm': 0.8292303871371115, 'learning_rate': 2.2550000000000004e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.03}
+0: {'loss': 0.5823, 'grad_norm': 0.7246674717655568, 'learning_rate': 2.7050000000000004e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.04}
+0: 711 [04:28<26:13,  2.32s/it]
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+0: {'loss': 0.5601, 'grad_norm': 0.7685808720049759, 'learning_rate': 3.1550000000000003e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.05}
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+0: {'loss': 0.5571, 'grad_norm': 0.7808588522979137, 'learning_rate': 4.055000000000001e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.07}
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+0: {'loss': 0.5341, 'grad_norm': 0.8642141374162505, 'learning_rate': 4.505e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.08}
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+0: {'loss': 0.5192, 'grad_norm': 0.8305549171618009, 'learning_rate': 4.955e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.08}
+0: {'loss': 0.5459, 'grad_norm': 0.8622685683478952, 'learning_rate': 5e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.09}
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+0: {'loss': 0.5358, 'grad_norm': 0.8178819353819496, 'learning_rate': 5e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.1}
+0: {'loss': 0.5179, 'grad_norm': 1.6879902769065394, 'learning_rate': 5e-06, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 67.45, 'epoch': 0.11}
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+0: {'loss': 0.4638, 'grad_norm': 0.7522821052393728, 'learning_rate': 6.330182698529928e-07, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 68.71, 'epoch': 0.58}
+0: {'loss': 0.456, 'grad_norm': 0.6485448600183656, 'learning_rate': 5.398536858604507e-07, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 68.71, 'epoch': 0.59}
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+0: {'loss': 0.4527, 'grad_norm': 0.6894880207361598, 'learning_rate': 5.011102391771039e-07, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 68.71, 'epoch': 0.6}
+0: [2025-11-24 00:42:38,710] [INFO] [axolotl.core.trainers.base._save:613] [PID:1912876] [RANK:0] Saving model checkpoint to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0/checkpoint-711
+0: [2025-11-24 00:42:45,711] [INFO] [axolotl.core.trainers.base._save:662] [PID:1912876] [RANK:0] Saving Trainer.data_collator.tokenizer by default as Trainer.processing_class is `None`
+0: {'train_runtime': 1863.7709, 'train_samples_per_second': 6.104, 'train_steps_per_second': 0.381, 'train_loss': 0.49791947950290727, 'memory/max_mem_active(gib)': 58.47, 'memory/max_mem_allocated(gib)': 57.09, 'memory/device_mem_reserved(gib)': 68.71, 'epoch': 0.6}
+0: 26<00:25,  2.34s/it]
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+0: .49s/it]
+0: [2025-11-24 00:42:49,004] [INFO] [axolotl.train.save_trained_model:228] [PID:1912876] [RANK:0] Training completed! Saving trained model to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0.
+0: [2025-11-24 00:42:51,675] [INFO] [axolotl.core.trainers.base._save:613] [PID:1912876] [RANK:0] Saving model checkpoint to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0
+0: [2025-11-24 00:42:58,432] [INFO] [axolotl.core.trainers.base._save:662] [PID:1912876] [RANK:0] Saving Trainer.data_collator.tokenizer by default as Trainer.processing_class is `None`
+0: [2025-11-24 00:42:59,125] [INFO] [axolotl.train.save_trained_model:350] [PID:1912876] [RANK:0] Model successfully saved to /lustre/fswork/projects/rech/dgo/udv55np/ift/Nemotron-Super-49B-v1_5/gemma-3-4b/0

special_tokens_map.json

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+{
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+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": {
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

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tokenizer.model

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