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RoBERTa_CSIC-Anomaly_Baseline
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5834
- Accuracy: 0.6683
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: 32
- eval_batch_size: 32
- 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 |
---|---|---|---|---|
0.6604 | 1.0 | 1094 | 0.6460 | 0.5898 |
0.6316 | 2.0 | 2188 | 0.6208 | 0.62 |
0.6156 | 3.0 | 3282 | 0.6119 | 0.6244 |
0.6081 | 4.0 | 4376 | 0.6008 | 0.6384 |
0.6021 | 5.0 | 5470 | 0.5945 | 0.6486 |
0.5983 | 6.0 | 6564 | 0.5925 | 0.6482 |
0.5955 | 7.0 | 7658 | 0.5860 | 0.664 |
0.5943 | 8.0 | 8752 | 0.5891 | 0.6502 |
0.5932 | 9.0 | 9846 | 0.5858 | 0.6582 |
0.5934 | 10.0 | 10940 | 0.5845 | 0.6622 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3