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roberta-base-roberta-base-TF-weight2-epoch5
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.5174
- Cls loss: 0.6899
- Lm loss: 4.1376
- Cls Accuracy: 0.5401
- Cls F1: 0.3788
- Cls Precision: 0.2917
- Cls Recall: 0.5401
- Perplexity: 62.65
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: 2
- 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 | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
---|---|---|---|---|---|---|---|---|---|---|
6.023 | 1.0 | 3470 | 5.6863 | 0.6910 | 4.3046 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 74.04 |
5.6871 | 2.0 | 6940 | 5.5897 | 0.6926 | 4.2045 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 66.99 |
5.5587 | 3.0 | 10410 | 5.5414 | 0.6905 | 4.1604 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 64.10 |
5.481 | 4.0 | 13880 | 5.5208 | 0.6900 | 4.1409 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.86 |
5.4338 | 5.0 | 17350 | 5.5174 | 0.6899 | 4.1376 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.65 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1