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sagemaker-bert-base-intent1018_2
This model is a fine-tuned version of asafaya/bert-base-arabic on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5145
- Accuracy: 0.9017
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: 3e-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
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 88 | 4.0951 | 0.0470 |
| No log | 2.0 | 176 | 3.7455 | 0.2158 |
| No log | 3.0 | 264 | 3.0505 | 0.4252 |
| No log | 4.0 | 352 | 2.0489 | 0.6303 |
| No log | 5.0 | 440 | 1.3342 | 0.7735 |
| 2.9556 | 6.0 | 528 | 0.9592 | 0.8162 |
| 2.9556 | 7.0 | 616 | 0.7623 | 0.8162 |
| 2.9556 | 8.0 | 704 | 0.6262 | 0.8547 |
| 2.9556 | 9.0 | 792 | 0.5145 | 0.9017 |
| 2.9556 | 10.0 | 880 | 0.5328 | 0.8846 |
| 2.9556 | 11.0 | 968 | 0.5137 | 0.8932 |
| 0.3206 | 12.0 | 1056 | 0.5190 | 0.8846 |
| 0.3206 | 13.0 | 1144 | 0.5158 | 0.8953 |
| 0.3206 | 14.0 | 1232 | 0.5053 | 0.8974 |
| 0.3206 | 15.0 | 1320 | 0.5140 | 0.8953 |
| 0.3206 | 16.0 | 1408 | 0.5108 | 0.8996 |
| 0.3206 | 17.0 | 1496 | 0.5282 | 0.8932 |
| 0.0381 | 18.0 | 1584 | 0.5278 | 0.8974 |
| 0.0381 | 19.0 | 1672 | 0.5224 | 0.8996 |
| 0.0381 | 20.0 | 1760 | 0.5226 | 0.8996 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.1
- Datasets 1.15.1
- Tokenizers 0.10.3
