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bert-finetuned-comp2
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9570
- Precision: 0.5169
- Recall: 0.6765
- F1: 0.5820
- Accuracy: 0.5820
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.8434 | 1.0 | 934 | 0.7147 | 0.4475 | 0.6252 | 0.5096 | 0.5096 |
| 0.6307 | 2.0 | 1868 | 0.5959 | 0.5058 | 0.6536 | 0.5585 | 0.5585 |
| 0.4691 | 3.0 | 2802 | 0.6555 | 0.4761 | 0.6865 | 0.5521 | 0.5521 |
| 0.334 | 4.0 | 3736 | 0.7211 | 0.5292 | 0.6682 | 0.5863 | 0.5863 |
| 0.2326 | 5.0 | 4670 | 0.8046 | 0.4886 | 0.6865 | 0.5682 | 0.5682 |
| 0.1625 | 6.0 | 5604 | 0.8650 | 0.4972 | 0.6851 | 0.5728 | 0.5728 |
| 0.1195 | 7.0 | 6538 | 0.9570 | 0.5169 | 0.6765 | 0.5820 | 0.5820 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
