bert-finetuned
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: 0.6658
- Accuracy: 0.7985
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 310 | 0.8028 | 0.7439 |
| 1.0075 | 2.0 | 620 | 0.6658 | 0.7985 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.11.0
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Model tree for Alec42/bert-base-uncased-finetune-accidents
Base model
google-bert/bert-base-uncased