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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold6
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_task4_fold6
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: 0.3809
- Qwk: 0.7212
- Mse: 0.3803
## 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 | 0.0290 | 2 | 3.5915 | 0.0135 | 3.5774 |
| No log | 0.0580 | 4 | 1.6728 | 0.1066 | 1.6543 |
| No log | 0.0870 | 6 | 0.9207 | 0.3071 | 0.9146 |
| No log | 0.1159 | 8 | 0.9451 | 0.4183 | 0.9392 |
| No log | 0.1449 | 10 | 1.0092 | 0.4761 | 1.0019 |
| No log | 0.1739 | 12 | 0.8467 | 0.4077 | 0.8353 |
| No log | 0.2029 | 14 | 0.7589 | 0.4123 | 0.7471 |
| No log | 0.2319 | 16 | 0.6332 | 0.4728 | 0.6243 |
| No log | 0.2609 | 18 | 0.6097 | 0.5641 | 0.6051 |
| No log | 0.2899 | 20 | 0.5389 | 0.5141 | 0.5354 |
| No log | 0.3188 | 22 | 0.5073 | 0.5047 | 0.5034 |
| No log | 0.3478 | 24 | 0.4996 | 0.5613 | 0.4954 |
| No log | 0.3768 | 26 | 0.4724 | 0.5931 | 0.4689 |
| No log | 0.4058 | 28 | 0.4067 | 0.6836 | 0.4044 |
| No log | 0.4348 | 30 | 0.4385 | 0.8033 | 0.4374 |
| No log | 0.4638 | 32 | 0.4624 | 0.8118 | 0.4616 |
| No log | 0.4928 | 34 | 0.4385 | 0.7922 | 0.4378 |
| No log | 0.5217 | 36 | 0.4184 | 0.6922 | 0.4169 |
| No log | 0.5507 | 38 | 0.4874 | 0.6033 | 0.4851 |
| No log | 0.5797 | 40 | 0.6206 | 0.5584 | 0.6172 |
| No log | 0.6087 | 42 | 0.7056 | 0.5187 | 0.7018 |
| No log | 0.6377 | 44 | 0.6335 | 0.5490 | 0.6305 |
| No log | 0.6667 | 46 | 0.4625 | 0.6195 | 0.4610 |
| No log | 0.6957 | 48 | 0.3971 | 0.7571 | 0.3968 |
| No log | 0.7246 | 50 | 0.4158 | 0.7849 | 0.4158 |
| No log | 0.7536 | 52 | 0.4127 | 0.7821 | 0.4127 |
| No log | 0.7826 | 54 | 0.4163 | 0.7855 | 0.4162 |
| No log | 0.8116 | 56 | 0.4055 | 0.7826 | 0.4053 |
| No log | 0.8406 | 58 | 0.3891 | 0.7730 | 0.3888 |
| No log | 0.8696 | 60 | 0.3833 | 0.7639 | 0.3829 |
| No log | 0.8986 | 62 | 0.3800 | 0.7588 | 0.3795 |
| No log | 0.9275 | 64 | 0.3788 | 0.7357 | 0.3783 |
| No log | 0.9565 | 66 | 0.3800 | 0.7299 | 0.3795 |
| No log | 0.9855 | 68 | 0.3809 | 0.7212 | 0.3803 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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