mbti-classification-bert-base-uncased
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: 2.3272
- Accuracy: 0.2924
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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Accuracy | Validation Loss |
---|---|---|---|---|
2.0851 | 1.0 | 13660 | 0.3052 | 2.0650 |
1.9902 | 2.0 | 27320 | 0.3105 | 2.0524 |
1.8139 | 3.0 | 40980 | 0.3029 | 2.1081 |
1.6191 | 4.0 | 54640 | 2.2604 | 0.2964 |
1.4893 | 5.0 | 68300 | 2.3272 | 0.2924 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu102
- Datasets 2.7.1
- Tokenizers 0.13.2
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