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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task2_fold3
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_task2_fold3
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: 0.2961
- Qwk: 0.3277
- Mse: 0.2961
## 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 | 1.1621 | 0.0229 | 1.1621 |
| No log | 0.0702 | 4 | 0.5340 | 0.1841 | 0.5340 |
| No log | 0.1053 | 6 | 0.5506 | 0.1500 | 0.5506 |
| No log | 0.1404 | 8 | 0.5057 | 0.1888 | 0.5057 |
| No log | 0.1754 | 10 | 0.4434 | 0.1993 | 0.4434 |
| No log | 0.2105 | 12 | 0.4171 | 0.2214 | 0.4171 |
| No log | 0.2456 | 14 | 0.3762 | 0.2316 | 0.3762 |
| No log | 0.2807 | 16 | 0.3295 | 0.2935 | 0.3295 |
| No log | 0.3158 | 18 | 0.3210 | 0.2948 | 0.3210 |
| No log | 0.3509 | 20 | 0.3093 | 0.2948 | 0.3093 |
| No log | 0.3860 | 22 | 0.3105 | 0.3062 | 0.3105 |
| No log | 0.4211 | 24 | 0.3464 | 0.3679 | 0.3464 |
| No log | 0.4561 | 26 | 0.3981 | 0.6151 | 0.3981 |
| No log | 0.4912 | 28 | 0.3851 | 0.6021 | 0.3851 |
| No log | 0.5263 | 30 | 0.3431 | 0.4831 | 0.3431 |
| No log | 0.5614 | 32 | 0.3017 | 0.3166 | 0.3017 |
| No log | 0.5965 | 34 | 0.2863 | 0.3277 | 0.2863 |
| No log | 0.6316 | 36 | 0.2906 | 0.3407 | 0.2906 |
| No log | 0.6667 | 38 | 0.2981 | 0.3509 | 0.2981 |
| No log | 0.7018 | 40 | 0.2999 | 0.3509 | 0.2999 |
| No log | 0.7368 | 42 | 0.2988 | 0.3391 | 0.2988 |
| No log | 0.7719 | 44 | 0.2970 | 0.3148 | 0.2970 |
| No log | 0.8070 | 46 | 0.2972 | 0.3126 | 0.2972 |
| No log | 0.8421 | 48 | 0.2982 | 0.3126 | 0.2982 |
| No log | 0.8772 | 50 | 0.2966 | 0.3158 | 0.2966 |
| No log | 0.9123 | 52 | 0.2961 | 0.3277 | 0.2961 |
| No log | 0.9474 | 54 | 0.2957 | 0.3286 | 0.2957 |
| No log | 0.9825 | 56 | 0.2961 | 0.3277 | 0.2961 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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