Model save

README.md

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+---
+license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: facebook/esm2_t12_35M_UR50D
+metrics:
+- accuracy
+model-index:
+- name: esm2_t12_35M-lora-binding-sites_2024-04-25_14-35-31
+  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. -->
+
+# esm2_t12_35M-lora-binding-sites_2024-04-25_14-35-31
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.3589
+- Accuracy: 0.8457
+
+## 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: 0.0005701568055793089
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 8893
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6703        | 1.0   | 24   | 0.6807          | 0.5820   |
+| 0.6449        | 2.0   | 48   | 0.6703          | 0.5820   |
+| 0.6659        | 3.0   | 72   | 0.6458          | 0.5977   |
+| 0.6432        | 4.0   | 96   | 0.6612          | 0.6328   |
+| 0.6322        | 5.0   | 120  | 0.6051          | 0.6523   |
+| 0.6176        | 6.0   | 144  | 0.6062          | 0.6504   |
+| 0.4904        | 7.0   | 168  | 0.5762          | 0.6777   |
+| 0.4426        | 8.0   | 192  | 0.5784          | 0.6953   |
+| 0.6014        | 9.0   | 216  | 0.5497          | 0.7148   |
+| 0.4484        | 10.0  | 240  | 0.5399          | 0.7227   |
+| 0.552         | 11.0  | 264  | 0.5142          | 0.7480   |
+| 0.3581        | 12.0  | 288  | 0.4395          | 0.7930   |
+| 0.3604        | 13.0  | 312  | 0.4201          | 0.8066   |
+| 0.2733        | 14.0  | 336  | 0.4107          | 0.8262   |
+| 0.2539        | 15.0  | 360  | 0.4373          | 0.8008   |
+| 0.3538        | 16.0  | 384  | 0.3954          | 0.8301   |
+| 0.4363        | 17.0  | 408  | 0.3852          | 0.8320   |
+| 0.3433        | 18.0  | 432  | 0.3735          | 0.8418   |
+| 0.2758        | 19.0  | 456  | 0.3685          | 0.8438   |
+| 0.2073        | 20.0  | 480  | 0.3860          | 0.8262   |
+| 0.3578        | 21.0  | 504  | 0.3689          | 0.8301   |
+| 0.3114        | 22.0  | 528  | 0.3626          | 0.8418   |
+| 0.3296        | 23.0  | 552  | 0.3621          | 0.8438   |
+| 0.276         | 24.0  | 576  | 0.3602          | 0.8457   |
+| 0.2583        | 25.0  | 600  | 0.3622          | 0.8457   |
+| 0.1917        | 26.0  | 624  | 0.3597          | 0.8477   |
+| 0.3588        | 27.0  | 648  | 0.3603          | 0.8477   |
+| 0.219         | 28.0  | 672  | 0.3606          | 0.8438   |
+| 0.3091        | 29.0  | 696  | 0.3586          | 0.8457   |
+| 0.2235        | 30.0  | 720  | 0.3589          | 0.8457   |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.39.3
+- Pytorch 2.2.1
+- Datasets 2.16.1
+- Tokenizers 0.15.2

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