jb_sytem_bin_judge_base_qa_wdo
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6013
- Accuracy: 0.7910
- Recall: 0.9244
- Precision: 0.6854
- F1: 0.7871
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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
---|---|---|---|---|---|---|---|
0.7797 | 1.0 | 1708 | 0.5605 | 0.7498 | 0.4643 | 0.8805 | 0.6080 |
0.662 | 2.0 | 3416 | 0.6802 | 0.5821 | 0.0 | 0.0 | 0.0 |
0.7345 | 3.0 | 5124 | 0.6811 | 0.5821 | 0.0 | 0.0 | 0.0 |
0.6475 | 4.0 | 6832 | 0.6817 | 0.5821 | 0.0 | 0.0 | 0.0 |
0.2504 | 5.0 | 8540 | 0.6013 | 0.7910 | 0.9244 | 0.6854 | 0.7871 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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