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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-v0
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-v0
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: 0.0513
- Spearmanr: 0.7389
## 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: 8
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.118 | 1.0 | 1180 | 0.1154 | 0.3185 |
| 0.1156 | 2.0 | 2360 | 0.1109 | 0.3383 |
| 0.1143 | 3.0 | 3540 | 0.1162 | 0.3194 |
| 0.1192 | 4.0 | 4720 | 0.1111 | 0.2974 |
| 0.1147 | 5.0 | 5900 | 0.1125 | 0.4043 |
| 0.1196 | 6.0 | 7080 | 0.1116 | 0.1580 |
| 0.1171 | 7.0 | 8260 | 0.1114 | 0.2923 |
| 0.1177 | 8.0 | 9440 | 0.1106 | 0.3592 |
| 0.1126 | 9.0 | 10620 | 0.1105 | 0.3724 |
| 0.1152 | 10.0 | 11800 | 0.1135 | 0.4947 |
| 0.1159 | 11.0 | 12980 | 0.1082 | 0.5113 |
| 0.0953 | 12.0 | 14160 | 0.0820 | 0.6096 |
| 0.0798 | 13.0 | 15340 | 0.0688 | 0.6442 |
| 0.074 | 14.0 | 16520 | 0.0710 | 0.6738 |
| 0.0704 | 15.0 | 17700 | 0.0816 | 0.6736 |
| 0.0678 | 16.0 | 18880 | 0.0596 | 0.7142 |
| 0.0599 | 17.0 | 20060 | 0.0689 | 0.7187 |
| 0.0568 | 18.0 | 21240 | 0.0566 | 0.7308 |
| 0.0534 | 19.0 | 22420 | 0.0518 | 0.7340 |
| 0.0522 | 20.0 | 23600 | 0.0513 | 0.7389 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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