fold_5
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: 0.0105
- Precision: 0.7304
- Recall: 0.6036
- F1: 0.6610
- Accuracy: 0.9993
- Roc Auc: 0.9957
- 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 |
---|---|---|---|---|---|---|---|---|---|
0.0252 | 1.0 | 632 | 0.0112 | 0.5890 | 0.5570 | 0.5726 | 0.9991 | 0.9975 | 0.9999 |
0.0105 | 2.0 | 1264 | 0.0105 | 0.7304 | 0.6036 | 0.6610 | 0.9993 | 0.9957 | 0.9999 |
0.0061 | 3.0 | 1896 | 0.0107 | 0.6488 | 0.7228 | 0.6838 | 0.9993 | 0.9956 | 0.9999 |
0.0027 | 4.0 | 2528 | 0.0114 | 0.7023 | 0.6969 | 0.6996 | 0.9993 | 0.9967 | 0.9999 |
0.0012 | 5.0 | 3160 | 0.0136 | 0.7841 | 0.6399 | 0.7047 | 0.9994 | 0.9945 | 0.9999 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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