arabert_baseline_mechanics_task4_fold0
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: 0.6930
- Qwk: 0.0
- Mse: 0.6930
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 | 1.0 | 2 | 2.5168 | -0.0385 | 2.5168 |
| No log | 2.0 | 4 | 0.7942 | 0.0625 | 0.7942 |
| No log | 3.0 | 6 | 0.4547 | 0.125 | 0.4547 |
| No log | 4.0 | 8 | 0.6479 | 0.3333 | 0.6479 |
| No log | 5.0 | 10 | 0.6637 | 0.5 | 0.6637 |
| No log | 6.0 | 12 | 0.7552 | 0.0 | 0.7552 |
| No log | 7.0 | 14 | 0.7813 | 0.1667 | 0.7813 |
| No log | 8.0 | 16 | 0.7229 | 0.0 | 0.7229 |
| No log | 9.0 | 18 | 0.6995 | 0.0 | 0.6995 |
| No log | 10.0 | 20 | 0.6930 | 0.0 | 0.6930 |
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_mechanics_task4_fold0
Base model
aubmindlab/bert-base-arabertv02