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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-v0.1 |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: Mistral_final_Task2_2.0 |
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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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# Mistral_final_Task2_2.0 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5570 |
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- Accuracy: 0.8943 |
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- Precision: 0.9184 |
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- Recall: 0.8661 |
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- F1 score: 0.8915 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| 0.9274 | 0.5450 | 200 | 0.6669 | 0.8371 | 0.9072 | 0.7521 | 0.8224 | |
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| 0.5321 | 1.0899 | 400 | 1.0293 | 0.7986 | 0.9861 | 0.6068 | 0.7513 | |
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| 0.4279 | 1.6349 | 600 | 1.0278 | 0.7586 | 0.6904 | 0.9402 | 0.7961 | |
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| 0.3054 | 2.1798 | 800 | 0.4428 | 0.8714 | 0.8575 | 0.8917 | 0.8743 | |
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| 0.2297 | 2.7248 | 1000 | 0.5243 | 0.8743 | 0.9428 | 0.7977 | 0.8642 | |
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| 0.1798 | 3.2698 | 1200 | 0.4710 | 0.8971 | 0.9043 | 0.8889 | 0.8966 | |
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| 0.158 | 3.8147 | 1400 | 0.5673 | 0.8986 | 0.9545 | 0.8376 | 0.8923 | |
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| 0.0921 | 4.3597 | 1600 | 0.5847 | 0.8743 | 0.8380 | 0.9288 | 0.8811 | |
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| 0.063 | 4.9046 | 1800 | 0.5570 | 0.8943 | 0.9184 | 0.8661 | 0.8915 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
