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