metadata
license: mit
base_model: Amna100/PreTraining-MLM
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fold_4
results: []
fold_4
This model is a fine-tuned version of Amna100/PreTraining-MLM on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0087
- Precision: 0.6815
- Recall: 0.6257
- F1: 0.6524
- Accuracy: 0.9994
- Roc Auc: 0.9964
- Pr Auc: 0.9999
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: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc |
|---|---|---|---|---|---|---|---|---|---|
| 0.0371 | 1.0 | 632 | 0.0188 | 0.8481 | 0.1959 | 0.3183 | 0.9991 | 0.9803 | 0.9996 |
| 0.0137 | 2.0 | 1264 | 0.0087 | 0.6815 | 0.6257 | 0.6524 | 0.9994 | 0.9964 | 0.9999 |
| 0.0078 | 3.0 | 1896 | 0.0094 | 0.6262 | 0.7690 | 0.6903 | 0.9993 | 0.9976 | 0.9999 |
| 0.0029 | 4.0 | 2528 | 0.0111 | 0.6216 | 0.7251 | 0.6694 | 0.9993 | 0.9965 | 0.9999 |
| 0.0018 | 5.0 | 3160 | 0.0125 | 0.8044 | 0.6374 | 0.7113 | 0.9995 | 0.9967 | 0.9999 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1