leetcode-solution-method-classifier-bert-base-uncased
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.5560
- Accuracy: 0.4106
Model description
More information needed
Intended uses & limitations
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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: 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 464 | 2.2015 | 0.3333 |
| 2.2822 | 2.0 | 928 | 2.0300 | 0.3478 |
| 2.1285 | 3.0 | 1392 | 1.9383 | 0.3623 |
| 1.8958 | 4.0 | 1856 | 1.8928 | 0.4010 |
| 1.5333 | 5.0 | 2320 | 2.1470 | 0.4010 |
| 1.1718 | 6.0 | 2784 | 2.2002 | 0.4396 |
| 0.7684 | 7.0 | 3248 | 2.7009 | 0.4300 |
| 0.48 | 8.0 | 3712 | 3.3770 | 0.3720 |
| 0.2755 | 9.0 | 4176 | 3.5560 | 0.4106 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Base model
google-bert/bert-base-uncased