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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task4_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_cross_relevance_task4_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: 0.1659
- Qwk: 0.0402
- Mse: 0.1659
## 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 | 0.0308 | 2 | 2.0522 | -0.0055 | 2.0522 |
| No log | 0.0615 | 4 | 0.6665 | -0.0084 | 0.6665 |
| No log | 0.0923 | 6 | 0.2290 | 0.0207 | 0.2290 |
| No log | 0.1231 | 8 | 0.1690 | 0.0796 | 0.1690 |
| No log | 0.1538 | 10 | 0.2100 | 0.0199 | 0.2100 |
| No log | 0.1846 | 12 | 0.4380 | 0.0228 | 0.4380 |
| No log | 0.2154 | 14 | 0.4146 | 0.0114 | 0.4146 |
| No log | 0.2462 | 16 | 0.4672 | 0.0164 | 0.4672 |
| No log | 0.2769 | 18 | 0.4548 | 0.0082 | 0.4548 |
| No log | 0.3077 | 20 | 0.3092 | 0.0166 | 0.3092 |
| No log | 0.3385 | 22 | 0.1656 | 0.0373 | 0.1656 |
| No log | 0.3692 | 24 | 0.1443 | 0.0155 | 0.1443 |
| No log | 0.4 | 26 | 0.1375 | 0.0344 | 0.1375 |
| No log | 0.4308 | 28 | 0.1319 | 0.0250 | 0.1319 |
| No log | 0.4615 | 30 | 0.1415 | 0.0270 | 0.1415 |
| No log | 0.4923 | 32 | 0.1730 | 0.0185 | 0.1730 |
| No log | 0.5231 | 34 | 0.2033 | 0.0185 | 0.2033 |
| No log | 0.5538 | 36 | 0.2320 | 0.0166 | 0.2320 |
| No log | 0.5846 | 38 | 0.2349 | 0.0149 | 0.2349 |
| No log | 0.6154 | 40 | 0.2136 | 0.0165 | 0.2136 |
| No log | 0.6462 | 42 | 0.1798 | 0.0165 | 0.1798 |
| No log | 0.6769 | 44 | 0.1596 | 0.0175 | 0.1596 |
| No log | 0.7077 | 46 | 0.1554 | 0.0243 | 0.1554 |
| No log | 0.7385 | 48 | 0.1612 | 0.0316 | 0.1612 |
| No log | 0.7692 | 50 | 0.1628 | 0.0261 | 0.1628 |
| No log | 0.8 | 52 | 0.1699 | 0.0317 | 0.1699 |
| No log | 0.8308 | 54 | 0.1702 | 0.0284 | 0.1702 |
| No log | 0.8615 | 56 | 0.1679 | 0.0334 | 0.1679 |
| No log | 0.8923 | 58 | 0.1678 | 0.0334 | 0.1678 |
| No log | 0.9231 | 60 | 0.1646 | 0.0436 | 0.1646 |
| No log | 0.9538 | 62 | 0.1648 | 0.0402 | 0.1648 |
| No log | 0.9846 | 64 | 0.1659 | 0.0402 | 0.1659 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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