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roberta-base-finetuned-cvbest2
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1263
- Precision: 0.6839
- Recall: 0.7805
- F1: 0.7290
- Accuracy: 0.9674
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: 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 17 | 0.4054 | 0.5 | 0.0010 | 0.0019 | 0.9038 |
| No log | 2.0 | 34 | 0.2859 | 0.3247 | 0.2660 | 0.2924 | 0.9201 |
| No log | 3.0 | 51 | 0.2169 | 0.3832 | 0.5774 | 0.4606 | 0.9358 |
| No log | 4.0 | 68 | 0.1691 | 0.4744 | 0.6634 | 0.5532 | 0.9504 |
| No log | 5.0 | 85 | 0.1571 | 0.5145 | 0.7360 | 0.6057 | 0.9495 |
| No log | 6.0 | 102 | 0.1458 | 0.5905 | 0.7669 | 0.6672 | 0.9596 |
| No log | 7.0 | 119 | 0.1304 | 0.6293 | 0.7718 | 0.6933 | 0.9630 |
| No log | 8.0 | 136 | 0.1284 | 0.6664 | 0.7901 | 0.7230 | 0.9666 |
| No log | 9.0 | 153 | 0.1263 | 0.6839 | 0.7805 | 0.7290 | 0.9674 |
| No log | 10.0 | 170 | 0.1295 | 0.6699 | 0.7930 | 0.7263 | 0.9669 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
