|
--- |
|
base_model: aubmindlab/bert-base-arabertv02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: arabert_baseline_mechanics_task7_fold1 |
|
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_mechanics_task7_fold1 |
|
|
|
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: 0.3250 |
|
- Qwk: 0.7258 |
|
- Mse: 0.3234 |
|
|
|
## 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 | 0.3333 | 2 | 0.9603 | 0.2687 | 0.9651 | |
|
| No log | 0.6667 | 4 | 0.6926 | 0.5364 | 0.7202 | |
|
| No log | 1.0 | 6 | 0.7727 | 0.6067 | 0.8086 | |
|
| No log | 1.3333 | 8 | 0.7221 | 0.3538 | 0.7310 | |
|
| No log | 1.6667 | 10 | 0.6375 | 0.4368 | 0.6487 | |
|
| No log | 2.0 | 12 | 0.5211 | 0.6263 | 0.5378 | |
|
| No log | 2.3333 | 14 | 0.4993 | 0.5911 | 0.5125 | |
|
| No log | 2.6667 | 16 | 0.5624 | 0.6433 | 0.5686 | |
|
| No log | 3.0 | 18 | 0.5828 | 0.6023 | 0.5851 | |
|
| No log | 3.3333 | 20 | 0.4962 | 0.6576 | 0.4985 | |
|
| No log | 3.6667 | 22 | 0.4100 | 0.6702 | 0.4135 | |
|
| No log | 4.0 | 24 | 0.4169 | 0.6702 | 0.4169 | |
|
| No log | 4.3333 | 26 | 0.4947 | 0.6509 | 0.4883 | |
|
| No log | 4.6667 | 28 | 0.6006 | 0.5556 | 0.5893 | |
|
| No log | 5.0 | 30 | 0.5615 | 0.6121 | 0.5504 | |
|
| No log | 5.3333 | 32 | 0.4063 | 0.6702 | 0.4018 | |
|
| No log | 5.6667 | 34 | 0.3483 | 0.7083 | 0.3470 | |
|
| No log | 6.0 | 36 | 0.3490 | 0.7258 | 0.3465 | |
|
| No log | 6.3333 | 38 | 0.3721 | 0.7258 | 0.3681 | |
|
| No log | 6.6667 | 40 | 0.3827 | 0.7337 | 0.3782 | |
|
| No log | 7.0 | 42 | 0.4201 | 0.6757 | 0.4135 | |
|
| No log | 7.3333 | 44 | 0.4186 | 0.6757 | 0.4120 | |
|
| No log | 7.6667 | 46 | 0.3821 | 0.7337 | 0.3775 | |
|
| No log | 8.0 | 48 | 0.3398 | 0.7258 | 0.3377 | |
|
| No log | 8.3333 | 50 | 0.3148 | 0.7258 | 0.3139 | |
|
| No log | 8.6667 | 52 | 0.3098 | 0.7258 | 0.3091 | |
|
| No log | 9.0 | 54 | 0.3110 | 0.7258 | 0.3101 | |
|
| No log | 9.3333 | 56 | 0.3160 | 0.7258 | 0.3149 | |
|
| No log | 9.6667 | 58 | 0.3224 | 0.7258 | 0.3209 | |
|
| No log | 10.0 | 60 | 0.3250 | 0.7258 | 0.3234 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
