fine_tuned_model_resume
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4879
- Accuracy: 0.8
- F1: 0.7892
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: 2
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|
| 1.6093 | 1.0 | 60 | 1.3628 | 0.4 | 0.2307 |
| 1.1424 | 2.0 | 120 | 0.8058 | 0.8333 | 0.8121 |
| 0.8537 | 3.0 | 180 | 1.0414 | 0.5333 | 0.4922 |
| 0.6039 | 4.0 | 240 | 0.5947 | 0.8333 | 0.8307 |
| 0.4326 | 5.0 | 300 | 0.4879 | 0.8 | 0.7892 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for zoedc/fine_tuned_model_resume
Base model
google-bert/bert-base-uncased