arabert_baseline_relevance_task3_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: 0.4533
- Qwk: 0.0
- Mse: 0.4662
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 | 0.6667 | 2 | 0.5670 | 0.0237 | 0.5557 |
No log | 1.3333 | 4 | 0.2239 | 0.0 | 0.2180 |
No log | 2.0 | 6 | 0.2912 | 0.0 | 0.2878 |
No log | 2.6667 | 8 | 0.3225 | 0.0 | 0.3205 |
No log | 3.3333 | 10 | 0.3274 | 0.0 | 0.3276 |
No log | 4.0 | 12 | 0.3260 | 0.0 | 0.3295 |
No log | 4.6667 | 14 | 0.3269 | 0.0 | 0.3323 |
No log | 5.3333 | 16 | 0.3627 | 0.0 | 0.3697 |
No log | 6.0 | 18 | 0.3851 | 0.0 | 0.3932 |
No log | 6.6667 | 20 | 0.3452 | 0.0 | 0.3543 |
No log | 7.3333 | 22 | 0.3589 | 0.0 | 0.3692 |
No log | 8.0 | 24 | 0.3714 | 0.0 | 0.3825 |
No log | 8.6667 | 26 | 0.4113 | 0.0 | 0.4233 |
No log | 9.3333 | 28 | 0.4400 | 0.0 | 0.4526 |
No log | 10.0 | 30 | 0.4533 | 0.0 | 0.4662 |
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_task3_fold1
Base model
aubmindlab/bert-base-arabertv02