Dagobert42/mobilebert-uncased-biored-finetuned
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: 1.0264
- Accuracy: 0.7163
- Precision: 0.1023
- Recall: 0.1429
- F1: 0.1192
- Weighted F1: 0.5979
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 | 13 | 1.6911 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 2.0 | 26 | 1.2080 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 3.0 | 39 | 1.0905 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 4.0 | 52 | 1.0400 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 5.0 | 65 | 1.0439 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 6.0 | 78 | 1.0288 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 7.0 | 91 | 1.0259 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 8.0 | 104 | 1.0180 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 9.0 | 117 | 1.0229 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
No log | 10.0 | 130 | 1.0186 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.15.0
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