L_Roberta3
This model is a fine-tuned version of
distilroberta-base on the None dataset.
It achieves the following results on the evaluation set:
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Loss: 0.2095
-
Accuracy: 0.9555
-
F1: 0.9555
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Precision: 0.9555
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Recall: 0.9555
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C Report: precision recall f1-score support
0 0.97 0.95 0.96 876
1 0.94 0.97 0.95 696
accuracy 0.96 1572
macro avg 0.95 0.96 0.96 1572
weighted avg 0.96 0.96 0.96 1572
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C Matrix: None
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | C Report | C Matrix |
|---|
| 0.2674 | 1.0 | 329 | 0.2436 | 0.9389 | 0.9389 | 0.9389 | 0.9389 | precision recall f1-score support | |
0 0.94 0.95 0.95 876
1 0.94 0.92 0.93 696
accuracy 0.94 1572
macro avg 0.94 0.94 0.94 1572
weighted avg 0.94 0.94 0.94 1572
| None |
| 0.1377 | 2.0 | 658 | 0.1506 | 0.9408 | 0.9408 | 0.9408 | 0.9408 | precision recall f1-score support
0 0.97 0.92 0.95 876
1 0.91 0.96 0.94 696
accuracy 0.94 1572
macro avg 0.94 0.94 0.94 1572
weighted avg 0.94 0.94 0.94 1572
| None |
| 0.0898 | 3.0 | 987 | 0.1491 | 0.9548 | 0.9548 | 0.9548 | 0.9548 | precision recall f1-score support
0 0.96 0.96 0.96 876
1 0.95 0.95 0.95 696
accuracy 0.95 1572
macro avg 0.95 0.95 0.95 1572
weighted avg 0.95 0.95 0.95 1572
| None |
| 0.0543 | 4.0 | 1316 | 0.1831 | 0.9561 | 0.9561 | 0.9561 | 0.9561 | precision recall f1-score support
0 0.97 0.95 0.96 876
1 0.94 0.96 0.95 696
accuracy 0.96 1572
macro avg 0.95 0.96 0.96 1572
weighted avg 0.96 0.96 0.96 1572
| None |
| 0.0394 | 5.0 | 1645 | 0.2095 | 0.9555 | 0.9555 | 0.9555 | 0.9555 | precision recall f1-score support
0 0.97 0.95 0.96 876
1 0.94 0.97 0.95 696
accuracy 0.96 1572
macro avg 0.95 0.96 0.96 1572
weighted avg 0.96 0.96 0.96 1572
| None |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1
