metadata
license: mit
base_model: facebook/esm2_t30_150M_UR50D
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: esm2_t30_150M_UR50D-finetuned-SO2F
results: []
esm2_t30_150M_UR50D-finetuned-SO2F
This model is a fine-tuned version of facebook/esm2_t30_150M_UR50D on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6608
- Accuracy: 0.7158
- Precision: 0.1682
- Recall: 0.5068
- F1: 0.2526
- Auc: 0.6223
- Mcc: 0.1585
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | Mcc |
|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 108 | 0.6768 | 0.6886 | 0.1465 | 0.4740 | 0.2238 | 0.5925 | 0.1175 |
| No log | 2.0 | 216 | 0.6646 | 0.6935 | 0.1628 | 0.5397 | 0.2502 | 0.6247 | 0.1573 |
| No log | 3.0 | 324 | 0.6608 | 0.7158 | 0.1682 | 0.5068 | 0.2526 | 0.6223 | 0.1585 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2