| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Qwen/Qwen3-0.6B-Base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - timarni/mmlu-stem-alpaca |
| model-index: |
| - name: outputs/qwen3_mmlu_alpaca_lr_5e-5 |
| 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: `0.9.2` |
| ```yaml |
| base_model: Qwen/Qwen3-0.6B-Base |
| # Automatically upload checkpoint and final model to HF |
| # hub_model_id: username/custom_model_name |
| |
| plugins: |
| - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin |
| strict: false |
| |
| chat_template: qwen3 |
| datasets: |
| - path: timarni/mmlu-stem-alpaca |
| type: alpaca |
| split: train |
| |
| val_set_size: 0.15 |
| output_dir: ./outputs/qwen3_mmlu_alpaca_lr_5e-5 |
| dataset_prepared_path: last_run_prepared |
| |
| sequence_len: 4096 #2048 |
| sample_packing: true |
| eval_sample_packing: true |
| pad_to_sequence_len: true |
| |
| wandb_project: mnlp_project |
| wandb_entity: tim-arni |
| wandb_watch: |
| wandb_name: qwen3-0.6B-mmlu_alpaca_style_lr_5e-5 |
| wandb_log_model: |
| |
| gradient_accumulation_steps: 2 |
| micro_batch_size: 1 |
| num_epochs: 5 |
| optimizer: adamw_torch |
| lr_scheduler: cosine |
| learning_rate: 0.00005 # 0.0002 |
| |
| bf16: auto |
| tf32: true |
| |
| gradient_checkpointing: offload |
| gradient_checkpointing_kwargs: |
| use_reentrant: false |
| resume_from_checkpoint: |
| logging_steps: 1 |
| flash_attention: true |
| |
| warmup_steps: 10 |
| evals_per_epoch: 4 |
| saves_per_epoch: 1 |
| weight_decay: 0.0 |
| special_tokens: |
| |
| ``` |
|
|
| </details><br> |
|
|
| # outputs/qwen3_mmlu_alpaca_lr_5e-5 |
|
|
| This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on the timarni/mmlu-stem-alpaca dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2293 |
|
|
| ## 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-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 4 |
| - total_eval_batch_size: 2 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - num_epochs: 5.0 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.5211 | 0.0952 | 1 | 0.5254 | |
| | 0.3878 | 0.2857 | 3 | 0.2026 | |
| | 0.0918 | 0.5714 | 6 | 0.1485 | |
| | 0.108 | 0.8571 | 9 | 0.1240 | |
| | 0.116 | 1.0952 | 12 | 0.1226 | |
| | 0.0992 | 1.3810 | 15 | 0.1217 | |
| | 0.0803 | 1.6667 | 18 | 0.2010 | |
| | 0.0557 | 1.9524 | 21 | 0.1384 | |
| | 0.0627 | 2.1905 | 24 | 0.1467 | |
| | 0.0315 | 2.4762 | 27 | 0.1556 | |
| | 0.0454 | 2.7619 | 30 | 0.2070 | |
| | 0.0118 | 3.0 | 33 | 0.2289 | |
| | 0.0461 | 3.2857 | 36 | 0.2317 | |
| | 0.0082 | 3.5714 | 39 | 0.2292 | |
| | 0.029 | 3.8571 | 42 | 0.2290 | |
| | 0.0138 | 4.0952 | 45 | 0.2299 | |
| | 0.0178 | 4.3810 | 48 | 0.2293 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.5.1 |
| - Tokenizers 0.21.1 |
| |
