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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_organization_task1_fold2
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_organization_task1_fold2
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: 1.1151
- Qwk: 0.0397
- Mse: 1.1151
## 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 | 8.1063 | 0.0 | 8.1063 |
| No log | 0.0615 | 4 | 4.3611 | 0.0014 | 4.3611 |
| No log | 0.0923 | 6 | 2.2521 | 0.0584 | 2.2521 |
| No log | 0.1231 | 8 | 1.4384 | 0.0131 | 1.4384 |
| No log | 0.1538 | 10 | 1.0665 | 0.1602 | 1.0665 |
| No log | 0.1846 | 12 | 1.0608 | 0.0513 | 1.0608 |
| No log | 0.2154 | 14 | 1.0636 | 0.0036 | 1.0636 |
| No log | 0.2462 | 16 | 1.0686 | 0.0036 | 1.0686 |
| No log | 0.2769 | 18 | 1.0668 | 0.0036 | 1.0668 |
| No log | 0.3077 | 20 | 1.0565 | 0.0036 | 1.0565 |
| No log | 0.3385 | 22 | 1.0769 | 0.0289 | 1.0769 |
| No log | 0.3692 | 24 | 1.0972 | 0.0487 | 1.0972 |
| No log | 0.4 | 26 | 1.1159 | 0.0549 | 1.1159 |
| No log | 0.4308 | 28 | 1.1270 | 0.0151 | 1.1270 |
| No log | 0.4615 | 30 | 1.1101 | 0.0506 | 1.1101 |
| No log | 0.4923 | 32 | 1.0734 | 0.0639 | 1.0734 |
| No log | 0.5231 | 34 | 1.0767 | 0.0 | 1.0767 |
| No log | 0.5538 | 36 | 1.0893 | -0.0185 | 1.0893 |
| No log | 0.5846 | 38 | 1.0994 | -0.0366 | 1.0994 |
| No log | 0.6154 | 40 | 1.1021 | -0.0710 | 1.1021 |
| No log | 0.6462 | 42 | 1.1002 | -0.0366 | 1.1002 |
| No log | 0.6769 | 44 | 1.1002 | -0.0366 | 1.1002 |
| No log | 0.7077 | 46 | 1.0992 | -0.0366 | 1.0992 |
| No log | 0.7385 | 48 | 1.0933 | -0.0366 | 1.0933 |
| No log | 0.7692 | 50 | 1.0949 | 0.0170 | 1.0949 |
| No log | 0.8 | 52 | 1.1043 | 0.0338 | 1.1043 |
| No log | 0.8308 | 54 | 1.1170 | 0.0169 | 1.1170 |
| No log | 0.8615 | 56 | 1.1228 | 0.0651 | 1.1228 |
| No log | 0.8923 | 58 | 1.1212 | 0.0474 | 1.1212 |
| No log | 0.9231 | 60 | 1.1220 | 0.0474 | 1.1220 |
| No log | 0.9538 | 62 | 1.1176 | 0.0397 | 1.1176 |
| No log | 0.9846 | 64 | 1.1151 | 0.0397 | 1.1151 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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