|
--- |
|
base_model: aubmindlab/bert-base-arabertv02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: arabert_baseline_organization_task8_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_organization_task8_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: 0.4941 |
|
- Qwk: 0.6010 |
|
- Mse: 0.4941 |
|
|
|
## 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 | 1.4026 | 0.0558 | 1.4026 | |
|
| No log | 1.0 | 4 | 1.1702 | 0.0 | 1.1702 | |
|
| No log | 1.5 | 6 | 1.0793 | -0.0294 | 1.0793 | |
|
| No log | 2.0 | 8 | 1.0475 | 0.4031 | 1.0475 | |
|
| No log | 2.5 | 10 | 0.9473 | 0.5191 | 0.9473 | |
|
| No log | 3.0 | 12 | 0.8743 | 0.3158 | 0.8743 | |
|
| No log | 3.5 | 14 | 0.7934 | 0.3158 | 0.7934 | |
|
| No log | 4.0 | 16 | 0.6914 | 0.4324 | 0.6914 | |
|
| No log | 4.5 | 18 | 0.6177 | 0.4940 | 0.6177 | |
|
| No log | 5.0 | 20 | 0.5611 | 0.4940 | 0.5611 | |
|
| No log | 5.5 | 22 | 0.5294 | 0.5714 | 0.5294 | |
|
| No log | 6.0 | 24 | 0.5033 | 0.5670 | 0.5033 | |
|
| No log | 6.5 | 26 | 0.4918 | 0.6010 | 0.4918 | |
|
| No log | 7.0 | 28 | 0.4919 | 0.6010 | 0.4919 | |
|
| No log | 7.5 | 30 | 0.4963 | 0.6010 | 0.4963 | |
|
| No log | 8.0 | 32 | 0.4997 | 0.6010 | 0.4997 | |
|
| No log | 8.5 | 34 | 0.4990 | 0.6010 | 0.4990 | |
|
| No log | 9.0 | 36 | 0.4963 | 0.6010 | 0.4963 | |
|
| No log | 9.5 | 38 | 0.4948 | 0.6010 | 0.4948 | |
|
| No log | 10.0 | 40 | 0.4941 | 0.6010 | 0.4941 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
