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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_cross_relevance_task1_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: 0.1907
- Qwk: 0.0246
- Mse: 0.1907
## 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 | 0.0351 | 2 | 1.1829 | -0.0050 | 1.1829 |
| No log | 0.0702 | 4 | 0.2409 | 0.0099 | 0.2409 |
| No log | 0.1053 | 6 | 0.1676 | -0.0484 | 0.1676 |
| No log | 0.1404 | 8 | 0.1570 | 0.0130 | 0.1570 |
| No log | 0.1754 | 10 | 0.3161 | 0.0173 | 0.3161 |
| No log | 0.2105 | 12 | 0.6111 | 0.0144 | 0.6111 |
| No log | 0.2456 | 14 | 0.4643 | 0.0505 | 0.4643 |
| No log | 0.2807 | 16 | 0.3698 | 0.0345 | 0.3698 |
| No log | 0.3158 | 18 | 0.2920 | 0.0181 | 0.2920 |
| No log | 0.3509 | 20 | 0.2091 | 0.0235 | 0.2091 |
| No log | 0.3860 | 22 | 0.1792 | 0.0092 | 0.1792 |
| No log | 0.4211 | 24 | 0.1670 | 0.0386 | 0.1670 |
| No log | 0.4561 | 26 | 0.1654 | 0.0258 | 0.1654 |
| No log | 0.4912 | 28 | 0.1730 | 0.0081 | 0.1730 |
| No log | 0.5263 | 30 | 0.1851 | 0.0141 | 0.1851 |
| No log | 0.5614 | 32 | 0.2064 | 0.0092 | 0.2064 |
| No log | 0.5965 | 34 | 0.2253 | 0.0270 | 0.2253 |
| No log | 0.6316 | 36 | 0.2300 | 0.0355 | 0.2300 |
| No log | 0.6667 | 38 | 0.2391 | 0.0339 | 0.2391 |
| No log | 0.7018 | 40 | 0.2358 | 0.0339 | 0.2358 |
| No log | 0.7368 | 42 | 0.2370 | 0.0300 | 0.2370 |
| No log | 0.7719 | 44 | 0.2370 | 0.0361 | 0.2370 |
| No log | 0.8070 | 46 | 0.2312 | 0.0323 | 0.2312 |
| No log | 0.8421 | 48 | 0.2215 | 0.0323 | 0.2215 |
| No log | 0.8772 | 50 | 0.2101 | 0.0358 | 0.2101 |
| No log | 0.9123 | 52 | 0.2006 | 0.0212 | 0.2006 |
| No log | 0.9474 | 54 | 0.1943 | 0.0246 | 0.1943 |
| No log | 0.9825 | 56 | 0.1907 | 0.0246 | 0.1907 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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