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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: timarni/qwen3_s1k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- timarni/MNLP_STEM_IT_HARD |
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model-index: |
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- name: outputs/qwen3_s1k_it_hard |
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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: `0.9.2` |
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```yaml |
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base_model: timarni/qwen3_s1k |
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# Automatically upload checkpoint and final model to HF |
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# hub_model_id: username/custom_model_name |
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plugins: |
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin |
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strict: false |
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chat_template: qwen3 |
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datasets: |
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- path: timarni/MNLP_STEM_IT_HARD |
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type: alpaca |
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split: train |
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val_set_size: 0.15 |
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output_dir: ./outputs/qwen3_s1k_it_hard |
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dataset_prepared_path: last_run_prepared |
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sequence_len: 2048 # 4096 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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# To be sure that no LORA is done |
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adapter: null |
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lora: false |
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merge_lora: false |
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wandb_project: mnlp_project |
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wandb_entity: tim-arni |
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wandb_watch: |
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wandb_name: qwen3_s1k_it_hard |
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wandb_log_model: |
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gradient_accumulation_steps: 4 # 2 |
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micro_batch_size: 2 # 1 |
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num_epochs: 5 |
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optimizer: adamw_torch |
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lr_scheduler: cosine |
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learning_rate: 0.00001 # 0.00005 |
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cosine_min_lr_ratio: 0.1 |
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bf16: auto |
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tf32: true |
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gradient_checkpointing: offload |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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resume_from_checkpoint: |
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logging_steps: 1 |
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flash_attention: true |
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warmup_ratio: 0.03 |
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evals_per_epoch: 4 |
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saves_per_epoch: 2 |
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save_total_limit: 10 |
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weight_decay: 0.001 |
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special_tokens: |
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``` |
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</details><br> |
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# outputs/qwen3_s1k_it_hard |
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This model is a fine-tuned version of [timarni/qwen3_s1k](https://huggingface.co/timarni/qwen3_s1k) on the timarni/MNLP_STEM_IT_HARD dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1654 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 13 |
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- num_epochs: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.0345 | 0.0109 | 1 | 2.0409 | |
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| 0.1118 | 0.2514 | 23 | 0.1711 | |
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| 0.0848 | 0.5027 | 46 | 0.1647 | |
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| 0.0884 | 0.7541 | 69 | 0.1625 | |
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| 0.1029 | 1.0 | 92 | 0.1623 | |
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| 0.0555 | 1.2514 | 115 | 0.1616 | |
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| 0.0767 | 1.5027 | 138 | 0.1618 | |
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| 0.0743 | 1.7541 | 161 | 0.1612 | |
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| 0.0747 | 2.0 | 184 | 0.1619 | |
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| 0.0571 | 2.2514 | 207 | 0.1647 | |
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| 0.0543 | 2.5027 | 230 | 0.1628 | |
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| 0.0573 | 2.7541 | 253 | 0.1643 | |
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| 0.0601 | 3.0 | 276 | 0.1630 | |
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| 0.057 | 3.2514 | 299 | 0.1641 | |
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| 0.0438 | 3.5027 | 322 | 0.1647 | |
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| 0.0564 | 3.7541 | 345 | 0.1648 | |
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| 0.0677 | 4.0 | 368 | 0.1648 | |
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| 0.0519 | 4.2514 | 391 | 0.1656 | |
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| 0.0487 | 4.5027 | 414 | 0.1653 | |
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| 0.0714 | 4.7541 | 437 | 0.1654 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.5.1 |
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- Tokenizers 0.21.1 |
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