metadata
base_model: Rostlab/prot_bert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: prot_bert-fine-tuned-toxicity_3.1
results: []
prot_bert-fine-tuned-toxicity_3.1
This model is a fine-tuned version of Rostlab/prot_bert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6981
- Accuracy: 0.5484
- Precision: 0.3007
- Recall: 0.5484
- F1: 0.3884
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 |
|---|---|---|---|---|---|---|---|
| 0.6948 | 1.0 | 16 | 0.6957 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6957 | 2.0 | 32 | 0.6965 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6939 | 3.0 | 48 | 0.6989 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6924 | 4.0 | 64 | 0.6977 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6924 | 5.0 | 80 | 0.6976 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6928 | 6.0 | 96 | 0.6984 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6923 | 7.0 | 112 | 0.6976 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
| 0.6876 | 8.0 | 128 | 0.6981 | 0.5484 | 0.3007 | 0.5484 | 0.3884 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1