bert_base_uncased
This model is a fine-tuned version of bert-base-uncased on the word-puzzle dataset. It achieves the following results on the evaluation set:
- Loss: 0.4856
- Accuracy: 0.8500
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 23 | 1.0218 | 0.6000 |
| No log | 2.0 | 46 | 0.6112 | 0.7250 |
| No log | 3.0 | 69 | 0.4168 | 0.875 |
| No log | 4.0 | 92 | 0.4505 | 0.8500 |
| No log | 5.0 | 115 | 0.4856 | 0.8500 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
google-bert/bert-base-uncased