File size: 3,450 Bytes
de9e476 635748f de9e476 635748f de9e476 635748f de9e476 635748f de9e476 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task5_fold0
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_style_task5_fold0
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: 0.6425
- Qwk: 0.6667
- Mse: 0.6425
## 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 | 1.7460 | 0.1985 | 1.7460 |
| No log | 0.6667 | 4 | 1.5870 | 0.0 | 1.5870 |
| No log | 1.0 | 6 | 1.4018 | 0.0 | 1.4018 |
| No log | 1.3333 | 8 | 1.2599 | 0.0 | 1.2599 |
| No log | 1.6667 | 10 | 1.2011 | 0.1294 | 1.2011 |
| No log | 2.0 | 12 | 1.1822 | 0.2077 | 1.1822 |
| No log | 2.3333 | 14 | 1.1032 | 0.3860 | 1.1032 |
| No log | 2.6667 | 16 | 1.0087 | 0.3860 | 1.0087 |
| No log | 3.0 | 18 | 0.9075 | 0.5652 | 0.9075 |
| No log | 3.3333 | 20 | 0.8395 | 0.4898 | 0.8395 |
| No log | 3.6667 | 22 | 0.7981 | 0.4898 | 0.7981 |
| No log | 4.0 | 24 | 0.7479 | 0.5455 | 0.7479 |
| No log | 4.3333 | 26 | 0.7093 | 0.5455 | 0.7093 |
| No log | 4.6667 | 28 | 0.6855 | 0.6222 | 0.6855 |
| No log | 5.0 | 30 | 0.6929 | 0.5614 | 0.6929 |
| No log | 5.3333 | 32 | 0.7079 | 0.4813 | 0.7079 |
| No log | 5.6667 | 34 | 0.6704 | 0.6222 | 0.6704 |
| No log | 6.0 | 36 | 0.6443 | 0.5946 | 0.6443 |
| No log | 6.3333 | 38 | 0.6496 | 0.5946 | 0.6496 |
| No log | 6.6667 | 40 | 0.6556 | 0.6119 | 0.6556 |
| No log | 7.0 | 42 | 0.6527 | 0.5946 | 0.6527 |
| No log | 7.3333 | 44 | 0.6454 | 0.5946 | 0.6454 |
| No log | 7.6667 | 46 | 0.6421 | 0.6186 | 0.6421 |
| No log | 8.0 | 48 | 0.6433 | 0.6186 | 0.6433 |
| No log | 8.3333 | 50 | 0.6419 | 0.6352 | 0.6419 |
| No log | 8.6667 | 52 | 0.6369 | 0.6352 | 0.6369 |
| No log | 9.0 | 54 | 0.6384 | 0.6667 | 0.6384 |
| No log | 9.3333 | 56 | 0.6431 | 0.6667 | 0.6431 |
| No log | 9.6667 | 58 | 0.6432 | 0.6667 | 0.6432 |
| No log | 10.0 | 60 | 0.6425 | 0.6667 | 0.6425 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|