CRAB_bert_base_uncased_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: 1.0100
- F1: 0.7250
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 1.0219 | 1.0 | 2880 | 1.0762 | 0.6806 |
| 0.8456 | 2.0 | 5760 | 0.9188 | 0.6986 |
| 0.8018 | 3.0 | 8640 | 1.0030 | 0.7264 |
| 0.7287 | 4.0 | 11520 | 0.9955 | 0.7181 |
| 0.69 | 5.0 | 14400 | 1.0546 | 0.7167 |
| 0.7155 | 6.0 | 17280 | 1.0075 | 0.7208 |
| 0.6945 | 7.0 | 20160 | 0.9942 | 0.7208 |
| 0.7096 | 8.0 | 23040 | 1.0100 | 0.7250 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1