alephbert-base-finetuned-DSS-maskedLM
This model is a fine-tuned version of onlplab/alephbert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2593
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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 41 | 4.6030 |
| No log | 2.0 | 82 | 4.4223 |
| 4.6114 | 3.0 | 123 | 4.3730 |
| 4.6114 | 4.0 | 164 | 4.3006 |
| 4.3175 | 5.0 | 205 | 4.3046 |
| 4.3175 | 6.0 | 246 | 4.2191 |
| 4.3175 | 7.0 | 287 | 4.3107 |
| 4.1903 | 8.0 | 328 | 4.2090 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for yonatanlou/alephbert-base-finetuned-DSS-maskedLM
Base model
onlplab/alephbert-base