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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_relevance_task1_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: 0.2541
- Qwk: 0.2373
- Mse: 0.2539
## 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 | 0.0333 | 2 | 0.3369 | 0.1172 | 0.3369 |
| No log | 0.0667 | 4 | 0.4978 | 0.3977 | 0.4978 |
| No log | 0.1 | 6 | 0.4733 | 0.3519 | 0.4733 |
| No log | 0.1333 | 8 | 0.3071 | 0.0964 | 0.3071 |
| No log | 0.1667 | 10 | 0.2732 | 0.1475 | 0.2733 |
| No log | 0.2 | 12 | 0.2941 | 0.2325 | 0.2943 |
| No log | 0.2333 | 14 | 0.2888 | 0.2076 | 0.2890 |
| No log | 0.2667 | 16 | 0.2781 | 0.2076 | 0.2782 |
| No log | 0.3 | 18 | 0.3038 | 0.2583 | 0.3038 |
| No log | 0.3333 | 20 | 0.3106 | 0.2515 | 0.3105 |
| No log | 0.3667 | 22 | 0.2932 | 0.2691 | 0.2930 |
| No log | 0.4 | 24 | 0.2674 | 0.2167 | 0.2669 |
| No log | 0.4333 | 26 | 0.2571 | 0.2325 | 0.2564 |
| No log | 0.4667 | 28 | 0.2516 | 0.2282 | 0.2509 |
| No log | 0.5 | 30 | 0.2513 | 0.2352 | 0.2506 |
| No log | 0.5333 | 32 | 0.2536 | 0.2414 | 0.2531 |
| No log | 0.5667 | 34 | 0.2678 | 0.2304 | 0.2674 |
| No log | 0.6 | 36 | 0.2837 | 0.2448 | 0.2832 |
| No log | 0.6333 | 38 | 0.3006 | 0.2257 | 0.3000 |
| No log | 0.6667 | 40 | 0.3090 | 0.2226 | 0.3084 |
| No log | 0.7 | 42 | 0.2975 | 0.2250 | 0.2971 |
| No log | 0.7333 | 44 | 0.2897 | 0.2572 | 0.2894 |
| No log | 0.7667 | 46 | 0.2878 | 0.2779 | 0.2875 |
| No log | 0.8 | 48 | 0.2796 | 0.2786 | 0.2794 |
| No log | 0.8333 | 50 | 0.2697 | 0.2649 | 0.2695 |
| No log | 0.8667 | 52 | 0.2639 | 0.2578 | 0.2637 |
| No log | 0.9 | 54 | 0.2596 | 0.2436 | 0.2594 |
| No log | 0.9333 | 56 | 0.2564 | 0.2443 | 0.2562 |
| No log | 0.9667 | 58 | 0.2544 | 0.2373 | 0.2543 |
| No log | 1.0 | 60 | 0.2541 | 0.2373 | 0.2539 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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