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my_awesome_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8597
- F1: 0.5171
- Precision: 0.5205
- Recall: 0.52
- Accuracy: 0.52
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
---|---|---|---|---|---|---|---|
0.6451 | 1.0 | 752 | 0.7708 | 0.4699 | 0.5047 | 0.5035 | 0.5035 |
0.5828 | 2.0 | 1504 | 0.7702 | 0.5101 | 0.5106 | 0.5106 | 0.5106 |
0.5139 | 3.0 | 2256 | 0.8597 | 0.5171 | 0.5205 | 0.52 | 0.52 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2