bert-azahead-v1.1
This model is a fine-tuned version of bert-base-uncased on the azaheadhealth dataset. It achieves the following results on the evaluation set:
- Loss: 0.4785
- Accuracy: 0.7917
- F1: 0.6154
- Precision: 0.6667
- Recall: 0.5714
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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 | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.6318 | 1.0 | 10 | 0.5247 | 0.6667 | 0.0 | 0.0 | 0.0 |
0.5623 | 2.0 | 20 | 0.4065 | 0.7917 | 0.5455 | 0.75 | 0.4286 |
0.4688 | 3.0 | 30 | 0.3514 | 0.7917 | 0.5455 | 0.75 | 0.4286 |
0.4252 | 4.0 | 40 | 0.3224 | 0.8333 | 0.6667 | 0.8 | 0.5714 |
0.2409 | 5.0 | 50 | 0.4115 | 0.75 | 0.4 | 0.6667 | 0.2857 |
0.2196 | 6.0 | 60 | 0.3672 | 0.7917 | 0.6667 | 0.625 | 0.7143 |
0.1417 | 7.0 | 70 | 0.4441 | 0.7917 | 0.5455 | 0.75 | 0.4286 |
0.0842 | 8.0 | 80 | 0.4422 | 0.7917 | 0.6154 | 0.6667 | 0.5714 |
0.065 | 9.0 | 90 | 0.4556 | 0.7917 | 0.6154 | 0.6667 | 0.5714 |
0.0657 | 10.0 | 100 | 0.4785 | 0.7917 | 0.6154 | 0.6667 | 0.5714 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.13.2
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Model tree for zwellington/bert-azahead-v1.1
Base model
google-bert/bert-base-uncased
Finetuned
this model
Evaluation results
- Accuracy on azaheadhealthtest set self-reported0.792
- F1 on azaheadhealthtest set self-reported0.615
- Precision on azaheadhealthtest set self-reported0.667
- Recall on azaheadhealthtest set self-reported0.571