File size: 2,048 Bytes
c533417 9508829 c533417 9508829 c533417 9508829 c533417 9508829 c533417 |
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 |
---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_task4_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_vocabulary_task4_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: 1.1529
- Qwk: 0.1724
- Mse: 1.1529
## 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 | 1.0 | 2 | 3.1705 | 0.0704 | 3.1705 |
| No log | 2.0 | 4 | 1.2678 | 0.0123 | 1.2678 |
| No log | 3.0 | 6 | 0.6681 | 0.1111 | 0.6681 |
| No log | 4.0 | 8 | 0.7489 | 0.4839 | 0.7489 |
| No log | 5.0 | 10 | 0.9971 | 0.1724 | 0.9971 |
| No log | 6.0 | 12 | 1.2195 | 0.1724 | 1.2195 |
| No log | 7.0 | 14 | 1.2558 | 0.1724 | 1.2558 |
| No log | 8.0 | 16 | 1.1787 | 0.1724 | 1.1787 |
| No log | 9.0 | 18 | 1.1576 | 0.1724 | 1.1576 |
| No log | 10.0 | 20 | 1.1529 | 0.1724 | 1.1529 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|