tvcg_entity_classify
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8480
- Accuracy: 0.7300
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|---|---|---|---|---|
| 0.6871 | 1.0 | 2956 | 0.6645 | 0.7416 |
| 0.5965 | 2.0 | 5912 | 0.6812 | 0.7419 |
| 0.4933 | 3.0 | 8868 | 0.6970 | 0.7455 |
| 0.4167 | 4.0 | 11824 | 0.7904 | 0.7371 |
| 0.3254 | 5.0 | 14780 | 0.8480 | 0.7300 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
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Model tree for Yamei/tvcg_entity_classify
Base model
google-bert/bert-base-uncased