metadata
license: mit
base_model: Amna100/PreTraining-MLM
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fold_3
results: []
fold_3
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: 0.0104
- Precision: 0.6792
- Recall: 0.5870
- F1: 0.6297
- Accuracy: 0.9993
- Roc Auc: 0.9967
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc |
|---|---|---|---|---|---|---|---|---|---|
| 0.0252 | 1.0 | 711 | 0.0159 | 0.4538 | 0.6413 | 0.5315 | 0.9988 | 0.9944 | 0.9998 |
| 0.0095 | 2.0 | 1422 | 0.0104 | 0.6792 | 0.5870 | 0.6297 | 0.9993 | 0.9967 | 0.9999 |
| 0.003 | 3.0 | 2133 | 0.0106 | 0.6432 | 0.6957 | 0.6684 | 0.9993 | 0.9973 | 0.9999 |
| 0.0024 | 4.0 | 2844 | 0.0126 | 0.7006 | 0.6739 | 0.6870 | 0.9994 | 0.9960 | 0.9999 |
| 0.0004 | 5.0 | 3555 | 0.0148 | 0.7239 | 0.6413 | 0.6801 | 0.9994 | 0.9954 | 0.9999 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1