arabert_baseline_relevance_task8_fold1
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2901
- Qwk: 0.4096
- Mse: 0.2901
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
|---|---|---|---|---|---|
| No log | 0.5 | 2 | 0.6071 | -0.1667 | 0.6071 |
| No log | 1.0 | 4 | 0.6292 | -0.0548 | 0.6292 |
| No log | 1.5 | 6 | 0.5112 | 0.3467 | 0.5112 |
| No log | 2.0 | 8 | 0.2941 | 0.2000 | 0.2941 |
| No log | 2.5 | 10 | 0.2595 | 0.3171 | 0.2595 |
| No log | 3.0 | 12 | 0.3011 | 0.3171 | 0.3011 |
| No log | 3.5 | 14 | 0.2934 | 0.3171 | 0.2934 |
| No log | 4.0 | 16 | 0.2489 | 0.3171 | 0.2489 |
| No log | 4.5 | 18 | 0.2716 | 0.4096 | 0.2716 |
| No log | 5.0 | 20 | 0.3200 | 0.3099 | 0.3200 |
| No log | 5.5 | 22 | 0.3416 | 0.2000 | 0.3416 |
| No log | 6.0 | 24 | 0.3237 | 0.4096 | 0.3237 |
| No log | 6.5 | 26 | 0.2949 | 0.4096 | 0.2949 |
| No log | 7.0 | 28 | 0.2821 | 0.4096 | 0.2821 |
| No log | 7.5 | 30 | 0.2766 | 0.4096 | 0.2766 |
| No log | 8.0 | 32 | 0.2780 | 0.4096 | 0.2780 |
| No log | 8.5 | 34 | 0.2807 | 0.4096 | 0.2807 |
| No log | 9.0 | 36 | 0.2841 | 0.4096 | 0.2841 |
| No log | 9.5 | 38 | 0.2889 | 0.4096 | 0.2889 |
| No log | 10.0 | 40 | 0.2901 | 0.4096 | 0.2901 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for salbatarni/arabert_baseline_relevance_task8_fold1
Base model
aubmindlab/bert-base-arabertv02