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fine-tune-roberta-exist
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6927
- Accuracy: 0.7529
- F1: 0.7507
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 194 | 0.5439 | 0.7529 | 0.7267 |
No log | 2.0 | 388 | 0.4870 | 0.7587 | 0.7662 |
0.4612 | 3.0 | 582 | 0.6623 | 0.7384 | 0.6959 |
0.4612 | 4.0 | 776 | 1.0824 | 0.7035 | 0.6304 |
0.4612 | 5.0 | 970 | 1.1488 | 0.7442 | 0.7457 |
0.1986 | 6.0 | 1164 | 1.4686 | 0.7587 | 0.7726 |
0.1986 | 7.0 | 1358 | 1.7357 | 0.75 | 0.7362 |
0.0649 | 8.0 | 1552 | 1.6859 | 0.7558 | 0.7586 |
0.0649 | 9.0 | 1746 | 1.6838 | 0.7471 | 0.7418 |
0.0649 | 10.0 | 1940 | 1.6927 | 0.7529 | 0.7507 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2