model_upgrade
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6052
- Accuracy: 0.6467
- F1: 0.5656
- Precision: 0.5306
- Recall: 0.6467
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: 3e-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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 1.0 | 101 | 0.6449 | 0.6017 | 0.5169 | 0.4906 | 0.6017 |
No log | 2.0 | 202 | 0.6052 | 0.6467 | 0.5656 | 0.5306 | 0.6467 |
No log | 3.0 | 303 | 0.6169 | 0.6255 | 0.5427 | 0.5043 | 0.6255 |
No log | 4.0 | 404 | 0.6344 | 0.6342 | 0.5513 | 0.5153 | 0.6342 |
0.5711 | 5.0 | 505 | 0.6630 | 0.6317 | 0.5489 | 0.5106 | 0.6317 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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