|
--- |
|
base_model: aubmindlab/bert-base-arabertv02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: arabert_cross_vocabulary_task3_fold2 |
|
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_cross_vocabulary_task3_fold2 |
|
|
|
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: 1.2889 |
|
- Qwk: 0.1455 |
|
- Mse: 1.2889 |
|
|
|
## 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: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:| |
|
| No log | 0.0282 | 2 | 8.9247 | 0.0 | 8.9247 | |
|
| No log | 0.0563 | 4 | 6.0585 | -0.0018 | 6.0585 | |
|
| No log | 0.0845 | 6 | 3.3683 | 0.0 | 3.3683 | |
|
| No log | 0.1127 | 8 | 1.9295 | 0.0353 | 1.9295 | |
|
| No log | 0.1408 | 10 | 1.1575 | 0.0 | 1.1575 | |
|
| No log | 0.1690 | 12 | 0.8179 | 0.0531 | 0.8179 | |
|
| No log | 0.1972 | 14 | 0.7602 | -0.0155 | 0.7602 | |
|
| No log | 0.2254 | 16 | 0.7582 | -0.0014 | 0.7582 | |
|
| No log | 0.2535 | 18 | 0.7660 | 0.0643 | 0.7660 | |
|
| No log | 0.2817 | 20 | 0.7464 | 0.0434 | 0.7464 | |
|
| No log | 0.3099 | 22 | 0.7568 | 0.0 | 0.7568 | |
|
| No log | 0.3380 | 24 | 0.7822 | 0.0 | 0.7822 | |
|
| No log | 0.3662 | 26 | 0.8311 | 0.0 | 0.8311 | |
|
| No log | 0.3944 | 28 | 0.8980 | 0.0 | 0.8980 | |
|
| No log | 0.4225 | 30 | 0.9093 | 0.0 | 0.9093 | |
|
| No log | 0.4507 | 32 | 0.8669 | 0.0 | 0.8669 | |
|
| No log | 0.4789 | 34 | 0.8507 | 0.0 | 0.8507 | |
|
| No log | 0.5070 | 36 | 0.8627 | 0.0 | 0.8627 | |
|
| No log | 0.5352 | 38 | 0.8443 | 0.0 | 0.8443 | |
|
| No log | 0.5634 | 40 | 0.8722 | 0.0 | 0.8722 | |
|
| No log | 0.5915 | 42 | 0.9229 | 0.0 | 0.9229 | |
|
| No log | 0.6197 | 44 | 0.9827 | 0.0 | 0.9827 | |
|
| No log | 0.6479 | 46 | 1.0396 | 0.0 | 1.0396 | |
|
| No log | 0.6761 | 48 | 1.1196 | 0.0 | 1.1196 | |
|
| No log | 0.7042 | 50 | 1.1654 | 0.0 | 1.1654 | |
|
| No log | 0.7324 | 52 | 1.1934 | 0.0086 | 1.1934 | |
|
| No log | 0.7606 | 54 | 1.2497 | 0.0603 | 1.2497 | |
|
| No log | 0.7887 | 56 | 1.2723 | 0.0272 | 1.2723 | |
|
| No log | 0.8169 | 58 | 1.2595 | 0.1040 | 1.2595 | |
|
| No log | 0.8451 | 60 | 1.2516 | 0.1696 | 1.2516 | |
|
| No log | 0.8732 | 62 | 1.2442 | 0.1807 | 1.2442 | |
|
| No log | 0.9014 | 64 | 1.2514 | 0.1696 | 1.2514 | |
|
| No log | 0.9296 | 66 | 1.2627 | 0.1524 | 1.2627 | |
|
| No log | 0.9577 | 68 | 1.2780 | 0.1455 | 1.2780 | |
|
| No log | 0.9859 | 70 | 1.2889 | 0.1455 | 1.2889 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
