---
license: mit
tags:
- generated_from_keras_callback
base_model: facebook/esm2_t30_150M_UR50D
model-index:
- name: esm2_t30_150M_UR50D-finetuned-AMP_Antibacteria-classification
  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_t30_150M_UR50D-finetuned-AMP_Antibacteria-classification

This model is a fine-tuned version of [facebook/esm2_t30_150M_UR50D](https://huggingface.co/facebook/esm2_t30_150M_UR50D) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0433
- Train Accuracy: 0.9871
- Validation Loss: 0.7702
- Validation Accuracy: 0.8014
- Epoch: 19

## 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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.6498     | 0.6047         | 0.6345          | 0.6288              | 0     |
| 0.5714     | 0.6877         | 0.5871          | 0.6882              | 1     |
| 0.3898     | 0.8198         | 0.5698          | 0.7242              | 2     |
| 0.2481     | 0.8921         | 0.5758          | 0.7696              | 3     |
| 0.1838     | 0.9248         | 0.6483          | 0.7730              | 4     |
| 0.1475     | 0.9390         | 0.6187          | 0.7904              | 5     |
| 0.1147     | 0.9541         | 0.6663          | 0.8007              | 6     |
| 0.0948     | 0.9618         | 0.7591          | 0.7819              | 7     |
| 0.0800     | 0.9701         | 0.7534          | 0.7959              | 8     |
| 0.0709     | 0.9739         | 0.8595          | 0.7810              | 9     |
| 0.0629     | 0.9767         | 0.8192          | 0.7907              | 10    |
| 0.0578     | 0.9792         | 0.8855          | 0.7946              | 11    |
| 0.0532     | 0.9814         | 0.9993          | 0.7762              | 12    |
| 0.0586     | 0.9801         | 0.9058          | 0.7761              | 13    |
| 0.0534     | 0.9816         | 0.8338          | 0.7786              | 14    |
| 0.0508     | 0.9824         | 0.7899          | 0.8033              | 15    |
| 0.0472     | 0.9840         | 0.9000          | 0.7800              | 16    |
| 0.0441     | 0.9851         | 0.8732          | 0.7911              | 17    |
| 0.0486     | 0.9846         | 0.8166          | 0.8088              | 18    |
| 0.0433     | 0.9871         | 0.7702          | 0.8014              | 19    |


### Framework versions

- Transformers 4.40.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1