bert-base-uncased-finetuned-wls-manual-10ep-lower
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4076
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1089 | 0.93 | 7 | 1.9417 |
| 1.5952 | 2.0 | 15 | 1.5688 |
| 1.4717 | 2.93 | 22 | 1.4364 |
| 1.3673 | 4.0 | 30 | 1.4096 |
| 1.2666 | 4.93 | 37 | 1.2430 |
| 1.2398 | 6.0 | 45 | 1.2435 |
| 1.2056 | 6.93 | 52 | 1.2533 |
| 1.1372 | 8.0 | 60 | 1.3034 |
| 1.1384 | 8.93 | 67 | 1.2087 |
| 1.1148 | 9.33 | 70 | 1.2141 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.11.0+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for btamm12/bert-base-uncased-finetuned-wls-manual-10ep-lower
Base model
google-bert/bert-base-uncased