bert-classifier-v2
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: 0.2327
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2272 | 1.0 | 1238 | 0.2106 |
| 0.0014 | 2.0 | 2476 | 0.1867 |
| 0.001 | 3.0 | 3714 | 0.2077 |
| 0.0006 | 4.0 | 4952 | 0.2216 |
| 0.136 | 5.0 | 6190 | 0.2327 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for krishkpatil/bert-classifier-v2
Base model
google-bert/bert-base-uncased