End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B-Base
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- cyberbabooshka/MNLP_M2_mcqa_dataset
+model-index:
+- name: base_noreasoning
+  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: `0.10.0.dev0`
+```yaml
+base_model: Qwen/Qwen3-0.6B-Base
+hub_model_id: cyberbabooshka/base_noreasoning
+wandb_name: base
+
+tokenizer_type: AutoTokenizer
+load_in_8bit: false
+load_in_4bit: false
+
+num_processes: 64
+dataset_processes: 64
+dataset_prepared_path: last_run_prepared
+
+chat_template: jinja
+chat_template_jinja: >-
+  {%- for message in messages %}
+    {{- '<|im_start|>' + message.role + '\n' + message.content.lstrip('\n') + '<|im_end|>' + '\n' }}
+  {%- endfor %}
+  {%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+  {%- endif %}
+
+datasets:
+  - path: cyberbabooshka/MNLP_M2_mcqa_dataset
+    split: train
+    type: chat_template
+    field_messages: messages
+    train_on_eos: turn
+    train_on_eot: turn
+    message_property_mappings:
+      role: role
+      content: content
+    roles:
+      user:
+        - user
+      assistant:
+        - assistant
+
+test_datasets:
+  - path: cyberbabooshka/MNLP_M2_mcqa_dataset
+    split: test
+    type: chat_template
+    field_messages: messages
+    train_on_eos: turn
+    train_on_eot: turn
+    message_property_mappings:
+      role: role
+      content: content
+    roles:
+      user:
+        - user
+      assistant:
+        - assistant
+
+output_dir: ./outputs
+
+sequence_len: 2048
+batch_flattening: true
+sample_packing: false
+
+wandb_project: mnlp
+wandb_entity: aleksandr-dremov-epfl
+wandb_watch:
+wandb_log_model:
+
+gradient_accumulation_steps: 1
+eval_batch_size: 16
+micro_batch_size: 12
+
+optimizer: ademamix_8bit
+weight_decay: 0.01
+
+learning_rate: 0.00001
+warmup_steps: 500
+
+wsd_final_lr_factor: 0.0
+wsd_init_div_factor: 100
+wsd_fract_decay: 0.2
+wsd_decay_type: "sqrt"
+wsd_sqrt_power: 0.5
+wsd_cooldown_start_lr_factor: 1.0
+
+bf16: auto
+tf32: false
+
+torch_compile: true
+flash_attention: true
+gradient_checkpointing: false
+
+resume_from_checkpoint:
+auto_resume_from_checkpoints: true
+
+logging_steps: 16
+eval_steps: 2000
+save_steps: 1000
+max_steps: 35000
+num_epochs: 20000000
+save_total_limit: 2
+
+special_tokens:
+  eos_token: "<|im_end|>"
+  pad_token: "<|endoftext|>"
+
+eot_tokens:
+  - <|im_end|>
+
+plugins:
+  - axolotl_wsd.WSDSchedulerPlugin
+
+```
+
+</details><br>
+
+# base_noreasoning
+
+This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on the cyberbabooshka/MNLP_M2_mcqa_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7964
+
+## 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: 1e-05
+- train_batch_size: 12
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- total_train_batch_size: 24
+- total_eval_batch_size: 32
+- optimizer: Use OptimizerNames.ADEMAMIX_8BIT and the args are:
+No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- training_steps: 35000
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss |
+|:-------------:|:------:|:-----:|:---------------:|
+| No log        | 0.0000 | 1     | 0.9810          |
+| 0.8508        | 0.0556 | 2000  | 0.8516          |
+| 0.8877        | 0.1111 | 4000  | 0.8365          |
+| 0.8851        | 0.1667 | 6000  | 0.8281          |
+| 0.8193        | 0.2223 | 8000  | 0.8222          |
+| 0.8298        | 0.2778 | 10000 | 0.8177          |
+| 0.8439        | 0.3334 | 12000 | 0.8141          |
+| 0.8364        | 0.3890 | 14000 | 0.8111          |
+| 0.8015        | 0.4445 | 16000 | 0.8085          |
+| 0.8112        | 0.5001 | 18000 | 0.8062          |
+| 0.7972        | 0.5556 | 20000 | 0.8042          |
+| 0.8264        | 0.6112 | 22000 | 0.8024          |
+| 0.7728        | 0.6668 | 24000 | 0.8008          |
+| 0.7762        | 0.7223 | 26000 | 0.7992          |
+| 0.8185        | 0.7779 | 28000 | 0.7978          |
+| 0.8235        | 0.8335 | 30000 | 0.7967          |
+| 0.7812        | 0.8890 | 32000 | 0.7964          |
+| 0.7872        | 0.9446 | 34000 | 0.7964          |
+
+
+### Framework versions
+
+- Transformers 4.52.1
+- Pytorch 2.7.0+cu126
+- Datasets 3.5.0
+- Tokenizers 0.21.1