mental-bert-base-uncased-masked_finetuned-0517
This model is a fine-tuned version of mental/mental-bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5217
- Accuracy: 0.917
- F1: 0.9171
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 3000 | 0.2922 | 0.8993 | 0.8997 |
| No log | 2.0 | 6000 | 0.3964 | 0.9063 | 0.9069 |
| No log | 3.0 | 9000 | 0.4456 | 0.9197 | 0.9197 |
| No log | 4.0 | 12000 | 0.5217 | 0.917 | 0.9171 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3
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