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edos-2023-baseline-bert-base-uncased-label_category
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: 1.0354
- F1: 0.5675
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 1.1743 | 1.18 | 100 | 1.1120 | 0.1949 |
| 1.0197 | 2.35 | 200 | 1.0548 | 0.3307 |
| 0.8872 | 3.53 | 300 | 0.9621 | 0.4795 |
| 0.7117 | 4.71 | 400 | 0.9876 | 0.4947 |
| 0.6173 | 5.88 | 500 | 0.9615 | 0.5447 |
| 0.5015 | 7.06 | 600 | 0.9973 | 0.5512 |
| 0.4076 | 8.24 | 700 | 1.0052 | 0.5620 |
| 0.3381 | 9.41 | 800 | 1.0354 | 0.5675 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
