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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_t12_35M_UR50D |
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metrics: |
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- accuracy |
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model-index: |
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- name: esm2_t12_35M-lora-binding-sites_2024-04-25_14-35-31 |
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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_t12_35M-lora-binding-sites_2024-04-25_14-35-31 |
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This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co./facebook/esm2_t12_35M_UR50D) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3589 |
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- Accuracy: 0.8457 |
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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: 0.0005701568055793089 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 8893 |
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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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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6703 | 1.0 | 24 | 0.6807 | 0.5820 | |
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| 0.6449 | 2.0 | 48 | 0.6703 | 0.5820 | |
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| 0.6659 | 3.0 | 72 | 0.6458 | 0.5977 | |
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| 0.6432 | 4.0 | 96 | 0.6612 | 0.6328 | |
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| 0.6322 | 5.0 | 120 | 0.6051 | 0.6523 | |
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| 0.6176 | 6.0 | 144 | 0.6062 | 0.6504 | |
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| 0.4904 | 7.0 | 168 | 0.5762 | 0.6777 | |
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| 0.4426 | 8.0 | 192 | 0.5784 | 0.6953 | |
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| 0.6014 | 9.0 | 216 | 0.5497 | 0.7148 | |
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| 0.4484 | 10.0 | 240 | 0.5399 | 0.7227 | |
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| 0.552 | 11.0 | 264 | 0.5142 | 0.7480 | |
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| 0.3581 | 12.0 | 288 | 0.4395 | 0.7930 | |
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| 0.3604 | 13.0 | 312 | 0.4201 | 0.8066 | |
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| 0.2733 | 14.0 | 336 | 0.4107 | 0.8262 | |
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| 0.2539 | 15.0 | 360 | 0.4373 | 0.8008 | |
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| 0.3538 | 16.0 | 384 | 0.3954 | 0.8301 | |
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| 0.4363 | 17.0 | 408 | 0.3852 | 0.8320 | |
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| 0.3433 | 18.0 | 432 | 0.3735 | 0.8418 | |
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| 0.2758 | 19.0 | 456 | 0.3685 | 0.8438 | |
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| 0.2073 | 20.0 | 480 | 0.3860 | 0.8262 | |
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| 0.3578 | 21.0 | 504 | 0.3689 | 0.8301 | |
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| 0.3114 | 22.0 | 528 | 0.3626 | 0.8418 | |
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| 0.3296 | 23.0 | 552 | 0.3621 | 0.8438 | |
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| 0.276 | 24.0 | 576 | 0.3602 | 0.8457 | |
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| 0.2583 | 25.0 | 600 | 0.3622 | 0.8457 | |
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| 0.1917 | 26.0 | 624 | 0.3597 | 0.8477 | |
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| 0.3588 | 27.0 | 648 | 0.3603 | 0.8477 | |
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| 0.219 | 28.0 | 672 | 0.3606 | 0.8438 | |
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| 0.3091 | 29.0 | 696 | 0.3586 | 0.8457 | |
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| 0.2235 | 30.0 | 720 | 0.3589 | 0.8457 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
