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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task2_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_baseline_relevance_task2_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: 0.1509
- Qwk: 0.1747
- Mse: 0.1416
## 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 | 0.3333 | 2 | 0.7029 | -0.0252 | 0.7093 |
| No log | 0.6667 | 4 | 0.1462 | -0.1951 | 0.1344 |
| No log | 1.0 | 6 | 0.2440 | 0.0 | 0.2429 |
| No log | 1.3333 | 8 | 0.1359 | 0.0 | 0.1325 |
| No log | 1.6667 | 10 | 0.1162 | 0.0219 | 0.1100 |
| No log | 2.0 | 12 | 0.1085 | 0.0345 | 0.1016 |
| No log | 2.3333 | 14 | 0.1197 | 0.0 | 0.1139 |
| No log | 2.6667 | 16 | 0.1465 | 0.0 | 0.1427 |
| No log | 3.0 | 18 | 0.1499 | 0.0 | 0.1462 |
| No log | 3.3333 | 20 | 0.1428 | 0.0 | 0.1389 |
| No log | 3.6667 | 22 | 0.1187 | 0.0483 | 0.1125 |
| No log | 4.0 | 24 | 0.1323 | 0.1217 | 0.1220 |
| No log | 4.3333 | 26 | 0.1627 | -0.1667 | 0.1498 |
| No log | 4.6667 | 28 | 0.1511 | 0.2075 | 0.1392 |
| No log | 5.0 | 30 | 0.1317 | 0.1217 | 0.1222 |
| No log | 5.3333 | 32 | 0.1331 | 0.0637 | 0.1256 |
| No log | 5.6667 | 34 | 0.1407 | 0.0105 | 0.1341 |
| No log | 6.0 | 36 | 0.1544 | 0.0105 | 0.1484 |
| No log | 6.3333 | 38 | 0.1639 | 0.0219 | 0.1582 |
| No log | 6.6667 | 40 | 0.1595 | 0.0483 | 0.1529 |
| No log | 7.0 | 42 | 0.1480 | 0.0808 | 0.1402 |
| No log | 7.3333 | 44 | 0.1440 | 0.1000 | 0.1358 |
| No log | 7.6667 | 46 | 0.1462 | 0.1000 | 0.1382 |
| No log | 8.0 | 48 | 0.1490 | 0.1747 | 0.1404 |
| No log | 8.3333 | 50 | 0.1535 | 0.1747 | 0.1441 |
| No log | 8.6667 | 52 | 0.1570 | 0.0094 | 0.1473 |
| No log | 9.0 | 54 | 0.1553 | 0.0094 | 0.1456 |
| No log | 9.3333 | 56 | 0.1529 | 0.1747 | 0.1436 |
| No log | 9.6667 | 58 | 0.1515 | 0.1747 | 0.1422 |
| No log | 10.0 | 60 | 0.1509 | 0.1747 | 0.1416 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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