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correct_BERT_token_itr0_0.0001_webDiscourse_01_03_2022-15_47_14
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6542
- Precision: 0.0092
- Recall: 0.0403
- F1: 0.0150
- Accuracy: 0.7291
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: 0.0001
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 10 | 0.5856 | 0.0012 | 0.0125 | 0.0022 | 0.6950 |
| No log | 2.0 | 20 | 0.5933 | 0.0 | 0.0 | 0.0 | 0.7282 |
| No log | 3.0 | 30 | 0.5729 | 0.0051 | 0.025 | 0.0085 | 0.7155 |
| No log | 4.0 | 40 | 0.6178 | 0.0029 | 0.0125 | 0.0047 | 0.7143 |
| No log | 5.0 | 50 | 0.6707 | 0.0110 | 0.0375 | 0.0170 | 0.7178 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
