|
--- |
|
base_model: aubmindlab/bert-base-arabertv02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: arabert_baseline_grammar_task6_fold0 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# arabert_baseline_grammar_task6_fold0 |
|
|
|
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4892 |
|
- Qwk: 0.6051 |
|
- Mse: 0.4892 |
|
|
|
## 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 | 1.0890 | 0.2687 | 1.0890 | |
|
| No log | 1.0 | 4 | 0.7915 | 0.3000 | 0.7915 | |
|
| No log | 1.5 | 6 | 0.8650 | 0.3529 | 0.8650 | |
|
| No log | 2.0 | 8 | 0.7927 | 0.3529 | 0.7927 | |
|
| No log | 2.5 | 10 | 0.6821 | 0.2602 | 0.6821 | |
|
| No log | 3.0 | 12 | 0.6081 | 0.4793 | 0.6081 | |
|
| No log | 3.5 | 14 | 0.6266 | 0.5882 | 0.6266 | |
|
| No log | 4.0 | 16 | 0.7668 | 0.5191 | 0.7668 | |
|
| No log | 4.5 | 18 | 0.7382 | 0.6164 | 0.7382 | |
|
| No log | 5.0 | 20 | 0.5722 | 0.7651 | 0.5722 | |
|
| No log | 5.5 | 22 | 0.5444 | 0.6755 | 0.5444 | |
|
| No log | 6.0 | 24 | 0.5298 | 0.6755 | 0.5298 | |
|
| No log | 6.5 | 26 | 0.5351 | 0.7651 | 0.5351 | |
|
| No log | 7.0 | 28 | 0.5998 | 0.6957 | 0.5998 | |
|
| No log | 7.5 | 30 | 0.5874 | 0.6957 | 0.5874 | |
|
| No log | 8.0 | 32 | 0.5369 | 0.6216 | 0.5369 | |
|
| No log | 8.5 | 34 | 0.4961 | 0.6480 | 0.4961 | |
|
| No log | 9.0 | 36 | 0.4879 | 0.6051 | 0.4879 | |
|
| No log | 9.5 | 38 | 0.4895 | 0.6051 | 0.4895 | |
|
| No log | 10.0 | 40 | 0.4892 | 0.6051 | 0.4892 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
