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--- |
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library_name: peft |
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base_model: AnnaelleMyriam/SFT_M3_model |
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tags: |
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- mcqa |
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- question-answering |
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- sft |
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- lora |
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- qwen |
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- unsloth |
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- generated_from_trainer |
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model-index: |
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- name: MNLP_M3_mcqa_sft_model |
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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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# MNLP_M3_mcqa_sft_model |
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This model is a fine-tuned version of [AnnaelleMyriam/SFT_M3_model](https://huggingface.co/AnnaelleMyriam/SFT_M3_model) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5993 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.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_ratio: 0.05 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.3535 | 0.1352 | 250 | 0.4926 | |
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| 0.4864 | 0.2703 | 500 | 0.3696 | |
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| 0.342 | 0.4055 | 750 | 0.3518 | |
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| 0.3763 | 0.5407 | 1000 | 0.3259 | |
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| 0.3566 | 0.6759 | 1250 | 0.3335 | |
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| 0.2901 | 0.8110 | 1500 | 0.3195 | |
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| 0.3235 | 0.9462 | 1750 | 0.3060 | |
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| 0.2315 | 1.0811 | 2000 | 0.3930 | |
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| 0.2842 | 1.2163 | 2250 | 0.3920 | |
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| 0.2183 | 1.3514 | 2500 | 0.3796 | |
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| 0.1824 | 1.4866 | 2750 | 0.3979 | |
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| 0.1877 | 1.6218 | 3000 | 0.4335 | |
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| 0.1821 | 1.7570 | 3250 | 0.3981 | |
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| 0.2364 | 1.8921 | 3500 | 0.3922 | |
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| 0.1339 | 2.0270 | 3750 | 0.4119 | |
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| 0.1073 | 2.1622 | 4000 | 0.5467 | |
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| 0.0722 | 2.2974 | 4250 | 0.5596 | |
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| 0.113 | 2.4325 | 4500 | 0.5158 | |
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| 0.1467 | 2.5677 | 4750 | 0.4852 | |
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| 0.1675 | 2.7029 | 5000 | 0.5103 | |
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| 0.101 | 2.8381 | 5250 | 0.5661 | |
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| 0.1935 | 2.9732 | 5500 | 0.4946 | |
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| 0.1069 | 3.1081 | 5750 | 0.5844 | |
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| 0.0799 | 3.2433 | 6000 | 0.5681 | |
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| 0.0803 | 3.3785 | 6250 | 0.5795 | |
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| 0.0744 | 3.5137 | 6500 | 0.5935 | |
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| 0.0464 | 3.6488 | 6750 | 0.6010 | |
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| 0.0643 | 3.7840 | 7000 | 0.6009 | |
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| 0.0871 | 3.9192 | 7250 | 0.5993 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.52.4 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
