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---
library_name: transformers
license: mit
base_model: facebook/esm2_t33_650M_UR50D
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: esm2_t33_650M_UR50D-finetuned
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_t33_650M_UR50D-finetuned
This model is a fine-tuned version of [facebook/esm2_t33_650M_UR50D](https://huggingface.co/facebook/esm2_t33_650M_UR50D) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4409
- Tp: 539
- Tn: 617
- Fp: 47
- Fn: 93
- Accuracy: 0.8920
- Precision: 0.9198
- Recall: 0.8528
- F1-score: 0.8851
- Auc: 0.8910
- Mcc: 0.7854
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Tp | Tn | Fp | Fn | Accuracy | Precision | Recall | F1-score | Auc | Mcc |
|:-------------:|:-----:|:----:|:---------------:|:---:|:---:|:--:|:---:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
| 0.393 | 1.0 | 1296 | 0.3616 | 507 | 615 | 49 | 125 | 0.8657 | 0.9119 | 0.8022 | 0.8535 | 0.8642 | 0.7356 |
| 0.3052 | 2.0 | 2592 | 0.3159 | 536 | 608 | 56 | 96 | 0.8827 | 0.9054 | 0.8481 | 0.8758 | 0.8819 | 0.7664 |
| 0.166 | 3.0 | 3888 | 0.4409 | 539 | 617 | 47 | 93 | 0.8920 | 0.9198 | 0.8528 | 0.8851 | 0.8910 | 0.7854 |
### Framework versions
- Transformers 4.45.2
- Pytorch 1.13.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.1
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