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roberta-large-fisrt
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8066
- Accuracy: 0.692
- F1: 0.5562
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-06
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.6366 | 1.0 | 751 | 0.5295 | 0.772 | 0.6460 |
0.561 | 2.0 | 1502 | 0.5421 | 0.737 | 0.6460 |
0.4939 | 3.0 | 2253 | 0.6779 | 0.696 | 0.4685 |
0.4238 | 4.0 | 3004 | 0.7281 | 0.694 | 0.5565 |
0.3769 | 5.0 | 3755 | 0.8066 | 0.692 | 0.5562 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3