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---
base_model: Rostlab/prot_bert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: prot_bert-fine-tuned-toxicity_2.0.1
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. -->
# prot_bert-fine-tuned-toxicity_2.0.1
This model is a fine-tuned version of [Rostlab/prot_bert](https://huggingface.co/Rostlab/prot_bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4239
- Accuracy: 0.8387
- Precision: 0.8391
- Recall: 0.8387
- F1: 0.8380
## 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: 8
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6945 | 1.0 | 16 | 0.6730 | 0.7742 | 0.8401 | 0.7742 | 0.7558 |
| 0.6185 | 2.0 | 32 | 0.6087 | 0.8065 | 0.8093 | 0.8065 | 0.8044 |
| 0.5241 | 3.0 | 48 | 0.5501 | 0.8387 | 0.8391 | 0.8387 | 0.8380 |
| 0.466 | 4.0 | 64 | 0.5328 | 0.8387 | 0.8391 | 0.8387 | 0.8380 |
| 0.4281 | 5.0 | 80 | 0.6886 | 0.7097 | 0.7252 | 0.7097 | 0.6967 |
| 0.3393 | 6.0 | 96 | 0.4568 | 0.8387 | 0.8391 | 0.8387 | 0.8380 |
| 0.1909 | 7.0 | 112 | 0.4239 | 0.8387 | 0.8391 | 0.8387 | 0.8380 |
| 0.243 | 8.0 | 128 | 0.4323 | 0.8387 | 0.8391 | 0.8387 | 0.8380 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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