super_clean_model
This model is a fine-tuned version of FacebookAI/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2385
- Accuracy: 0.9485
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: 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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6712 | 0.04 | 100 | 0.7864 | 0.6115 |
0.4785 | 0.09 | 200 | 1.1828 | 0.7385 |
0.475 | 0.13 | 300 | 0.3719 | 0.888 |
0.3643 | 0.18 | 400 | 0.6170 | 0.887 |
0.3546 | 0.22 | 500 | 0.6397 | 0.9045 |
0.3796 | 0.27 | 600 | 0.2512 | 0.9435 |
0.3301 | 0.31 | 700 | 0.2626 | 0.9135 |
0.3343 | 0.36 | 800 | 0.4675 | 0.8745 |
0.3578 | 0.4 | 900 | 0.2701 | 0.903 |
0.2604 | 0.44 | 1000 | 0.2385 | 0.9485 |
0.3236 | 0.49 | 1100 | 1.9438 | 0.6565 |
0.3147 | 0.53 | 1200 | 1.2576 | 0.779 |
0.2758 | 0.58 | 1300 | 0.3486 | 0.9345 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu118
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for EndOfLe/super_clean_model
Base model
FacebookAI/roberta-large