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--- |
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license: mit |
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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: facebook/esm2_t6_8M_UR50D |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: esm2-t6-8M-lora-256-remote-homology-filtered |
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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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# esm2-t6-8M-lora-256-remote-homology-filtered |
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This model is a fine-tuned version of [facebook/esm2_t6_8M_UR50D](https://huggingface.co/facebook/esm2_t6_8M_UR50D) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5982 |
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- Precision: 0.6901 |
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- Recall: 0.6529 |
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- F1-score: 0.6709 |
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- Accuracy: 0.6788 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:| |
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| 0.6365 | 1.0 | 7969 | 0.6357 | 0.6218 | 0.7071 | 0.6617 | 0.6374 | |
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| 0.6046 | 2.0 | 15938 | 0.6102 | 0.6864 | 0.6149 | 0.6487 | 0.6660 | |
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| 0.6134 | 3.0 | 23907 | 0.6017 | 0.6887 | 0.6469 | 0.6672 | 0.6763 | |
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| 0.6108 | 4.0 | 31876 | 0.5986 | 0.6920 | 0.6468 | 0.6687 | 0.6785 | |
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| 0.5831 | 5.0 | 39845 | 0.5982 | 0.6901 | 0.6529 | 0.6709 | 0.6788 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
