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README.md
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---
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license: mit
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base_model: facebook/esm2_t12_35M_UR50D
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tags:
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- generated_from_trainer
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metrics:
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- spearmanr
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model-index:
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- name: esm2_t12_35M_UR50D-finetuned-rep7868aav2-v1
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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_UR50D-finetuned-rep7868aav2-v1
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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: 0.0505
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- Spearmanr: 0.7430
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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: 16
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- eval_batch_size: 32
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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: 20
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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 | Spearmanr |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|
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| 0.1227 | 1.0 | 590 | 0.1132 | 0.3426 |
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| 0.117 | 2.0 | 1180 | 0.1105 | 0.3945 |
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| 0.1177 | 3.0 | 1770 | 0.1150 | 0.2857 |
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| 0.1143 | 4.0 | 2360 | 0.1107 | 0.3518 |
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| 0.1176 | 5.0 | 2950 | 0.1133 | 0.3774 |
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| 0.117 | 6.0 | 3540 | 0.1115 | 0.3230 |
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| 0.1178 | 7.0 | 4130 | 0.1107 | 0.4432 |
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| 0.1146 | 8.0 | 4720 | 0.1105 | 0.4608 |
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| 0.1182 | 9.0 | 5310 | 0.1105 | 0.4004 |
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| 0.114 | 10.0 | 5900 | 0.1122 | 0.5124 |
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| 0.115 | 11.0 | 6490 | 0.1108 | 0.5551 |
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| 0.1152 | 12.0 | 7080 | 0.1091 | 0.5391 |
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| 0.1109 | 13.0 | 7670 | 0.0705 | 0.6234 |
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| 0.0888 | 14.0 | 8260 | 0.0633 | 0.6810 |
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| 0.0832 | 15.0 | 8850 | 0.0584 | 0.6952 |
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| 0.0705 | 16.0 | 9440 | 0.0585 | 0.7102 |
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| 0.0635 | 17.0 | 10030 | 0.0581 | 0.7167 |
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| 0.0606 | 18.0 | 10620 | 0.0525 | 0.7326 |
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| 0.0562 | 19.0 | 11210 | 0.0555 | 0.7403 |
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| 0.055 | 20.0 | 11800 | 0.0505 | 0.7430 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.17.1
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- Tokenizers 0.15.2
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