bert-large-uncased-detect-dep-v9
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5492
- Accuracy: 0.745
- F1: 0.8200
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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6247 | 1.0 | 1502 | 0.5405 | 0.748 | 0.8230 |
| 0.5825 | 2.0 | 3004 | 0.5492 | 0.745 | 0.8200 |
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 Trong-Nghia/bert-large-uncased-detect-dep-v9
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google-bert/bert-large-uncased
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