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minirbt-fin-finetuned
This model is a fine-tuned version of hfl/minirbt-h256 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4364
- Accuracy: 0.8180
- F1: 0.8172
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6341 | 1.0 | 22 | 0.5113 | 0.7679 | 0.7677 |
| 0.4449 | 2.0 | 44 | 0.4364 | 0.8180 | 0.8172 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.0.dev20230212
- Datasets 2.9.0
- Tokenizers 0.13.2
