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---
license: mit
base_model: facebook/esm2_t12_35M_UR50D
tags:
- generated_from_trainer
metrics:
- spearmanr
model-index:
- name: esm2_t12_35M_UR50D-finetuned-rep7868aav2-v1
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_UR50D-finetuned-rep7868aav2-v1
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: 0.0505
- Spearmanr: 0.7430
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spearmanr |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.1227 | 1.0 | 590 | 0.1132 | 0.3426 |
| 0.117 | 2.0 | 1180 | 0.1105 | 0.3945 |
| 0.1177 | 3.0 | 1770 | 0.1150 | 0.2857 |
| 0.1143 | 4.0 | 2360 | 0.1107 | 0.3518 |
| 0.1176 | 5.0 | 2950 | 0.1133 | 0.3774 |
| 0.117 | 6.0 | 3540 | 0.1115 | 0.3230 |
| 0.1178 | 7.0 | 4130 | 0.1107 | 0.4432 |
| 0.1146 | 8.0 | 4720 | 0.1105 | 0.4608 |
| 0.1182 | 9.0 | 5310 | 0.1105 | 0.4004 |
| 0.114 | 10.0 | 5900 | 0.1122 | 0.5124 |
| 0.115 | 11.0 | 6490 | 0.1108 | 0.5551 |
| 0.1152 | 12.0 | 7080 | 0.1091 | 0.5391 |
| 0.1109 | 13.0 | 7670 | 0.0705 | 0.6234 |
| 0.0888 | 14.0 | 8260 | 0.0633 | 0.6810 |
| 0.0832 | 15.0 | 8850 | 0.0584 | 0.6952 |
| 0.0705 | 16.0 | 9440 | 0.0585 | 0.7102 |
| 0.0635 | 17.0 | 10030 | 0.0581 | 0.7167 |
| 0.0606 | 18.0 | 10620 | 0.0525 | 0.7326 |
| 0.0562 | 19.0 | 11210 | 0.0555 | 0.7403 |
| 0.055 | 20.0 | 11800 | 0.0505 | 0.7430 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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