Dagobert42/mobilebert-uncased-biored-augmented
This model is a fine-tuned version of mobilebert-uncased on the bigbio/biored dataset. It achieves the following results on the evaluation set:
- Loss: 0.5602
- Accuracy: 0.8057
- Precision: 0.6022
- Recall: 0.4577
- F1: 0.5007
- Weighted F1: 0.7931
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 25 | 0.6641 | 0.7644 | 0.5563 | 0.3256 | 0.3768 | 0.7254 |
| No log | 2.0 | 50 | 0.6506 | 0.7728 | 0.5735 | 0.369 | 0.4057 | 0.7457 |
| No log | 3.0 | 75 | 0.6352 | 0.7779 | 0.5671 | 0.413 | 0.4527 | 0.768 |
| No log | 4.0 | 100 | 0.6147 | 0.7886 | 0.6221 | 0.4133 | 0.4523 | 0.7723 |
| No log | 5.0 | 125 | 0.6223 | 0.7885 | 0.6176 | 0.4051 | 0.4416 | 0.7684 |
| No log | 6.0 | 150 | 0.6020 | 0.7913 | 0.584 | 0.4496 | 0.4928 | 0.7811 |
| No log | 7.0 | 175 | 0.6081 | 0.7913 | 0.5508 | 0.4964 | 0.5183 | 0.7876 |
| No log | 8.0 | 200 | 0.5935 | 0.799 | 0.6333 | 0.4461 | 0.4926 | 0.7826 |
| No log | 9.0 | 225 | 0.6110 | 0.7941 | 0.5998 | 0.4656 | 0.5078 | 0.7825 |
| No log | 10.0 | 250 | 0.5990 | 0.798 | 0.6332 | 0.4564 | 0.5099 | 0.7777 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.15.0