---
license: mit
tags:
- generated_from_keras_callback
base_model: facebook/esm2_t12_35M_UR50D
model-index:
- name: esm2_t12_35M_UR50D-finetuned-AMP_Classification_AntiGramPositive_doublePositiveCase
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# esm2_t12_35M_UR50D-finetuned-AMP_Classification_AntiGramPositive_doublePositiveCase

This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0617
- Train Accuracy: 0.9772
- Validation Loss: 0.5210
- Validation Accuracy: 0.8551
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.4862     | 0.7800         | 0.4257          | 0.8218              | 0     |
| 0.3768     | 0.8474         | 0.3845          | 0.8478              | 1     |
| 0.2799     | 0.8950         | 0.3625          | 0.8643              | 2     |
| 0.2042     | 0.9241         | 0.3613          | 0.8617              | 3     |
| 0.1502     | 0.9427         | 0.3833          | 0.8745              | 4     |
| 0.1228     | 0.9545         | 0.3959          | 0.8719              | 5     |
| 0.0935     | 0.9650         | 0.4453          | 0.8682              | 6     |
| 0.0786     | 0.9692         | 0.4728          | 0.8711              | 7     |
| 0.0682     | 0.9750         | 0.4915          | 0.8727              | 8     |
| 0.0617     | 0.9772         | 0.5210          | 0.8551              | 9     |


### Framework versions

- Transformers 4.40.2
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1