testtest-19
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5631
- Accuracy: 0.8627
- F1: 0.9048
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 459 | 0.5077 | 0.8137 | 0.8707 |
0.5519 | 2.0 | 918 | 0.4666 | 0.8431 | 0.8954 |
0.3741 | 3.0 | 1377 | 0.5631 | 0.8627 | 0.9048 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2
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Dataset used to train diegoref/testtest-19
Evaluation results
- Accuracy on gluevalidation set self-reported0.863
- F1 on gluevalidation set self-reported0.905