metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hebert-finetuned-hebrew-metaphor
results: []
hebert-finetuned-hebrew-metaphor
This model is a fine-tuned version of avichr/heBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4682
- Accuracy: 0.9510
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 389 | 0.1813 | 0.9379 |
| 0.2546 | 2.0 | 778 | 0.2309 | 0.9479 |
| 0.08 | 3.0 | 1167 | 0.3342 | 0.9492 |
| 0.0298 | 4.0 | 1556 | 0.4076 | 0.9460 |
| 0.0298 | 5.0 | 1945 | 0.3803 | 0.9485 |
| 0.0105 | 6.0 | 2334 | 0.3674 | 0.9454 |
| 0.0077 | 7.0 | 2723 | 0.5356 | 0.9410 |
| 0.0088 | 8.0 | 3112 | 0.4776 | 0.9422 |
| 0.0044 | 9.0 | 3501 | 0.4258 | 0.9504 |
| 0.0044 | 10.0 | 3890 | 0.4305 | 0.9523 |
| 0.001 | 11.0 | 4279 | 0.4357 | 0.9548 |
| 0.0031 | 12.0 | 4668 | 0.4770 | 0.9473 |
| 0.0015 | 13.0 | 5057 | 0.4604 | 0.9523 |
| 0.0015 | 14.0 | 5446 | 0.4670 | 0.9510 |
| 0.0022 | 15.0 | 5835 | 0.4682 | 0.9510 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3