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---
license: mit
tags:
- generated_from_keras_callback
base_model: facebook/esm2_t30_150M_UR50D
model-index:
- name: esm2_t30_150M_UR50D-finetuned-AMP_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_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
|