File size: 3,482 Bytes
7501118 b91a4ed 7501118 b91a4ed 7501118 b91a4ed 7501118 b91a4ed 7501118 |
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_task1_fold1
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_task1_fold1
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: 0.4983
- Qwk: 0.5052
- Mse: 0.4984
## 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 | 5.8113 | -0.0102 | 5.7669 |
| No log | 0.6667 | 4 | 2.3576 | 0.0342 | 2.3554 |
| No log | 1.0 | 6 | 1.4911 | 0.0652 | 1.4969 |
| No log | 1.3333 | 8 | 0.7580 | 0.1021 | 0.7628 |
| No log | 1.6667 | 10 | 0.5619 | 0.2851 | 0.5662 |
| No log | 2.0 | 12 | 0.6485 | 0.0870 | 0.6536 |
| No log | 2.3333 | 14 | 1.0404 | 0.1138 | 1.0530 |
| No log | 2.6667 | 16 | 0.6654 | 0.2646 | 0.6722 |
| No log | 3.0 | 18 | 0.4343 | 0.3425 | 0.4348 |
| No log | 3.3333 | 20 | 0.4318 | 0.4057 | 0.4340 |
| No log | 3.6667 | 22 | 0.4542 | 0.4057 | 0.4579 |
| No log | 4.0 | 24 | 0.5421 | 0.3191 | 0.5486 |
| No log | 4.3333 | 26 | 0.4470 | 0.3780 | 0.4507 |
| No log | 4.6667 | 28 | 0.4369 | 0.5130 | 0.4397 |
| No log | 5.0 | 30 | 0.4435 | 0.5130 | 0.4458 |
| No log | 5.3333 | 32 | 0.4758 | 0.6488 | 0.4772 |
| No log | 5.6667 | 34 | 0.5072 | 0.5130 | 0.5092 |
| No log | 6.0 | 36 | 0.5982 | 0.4160 | 0.6024 |
| No log | 6.3333 | 38 | 0.6201 | 0.3368 | 0.6243 |
| No log | 6.6667 | 40 | 0.5336 | 0.4731 | 0.5349 |
| No log | 7.0 | 42 | 0.5080 | 0.6613 | 0.5072 |
| No log | 7.3333 | 44 | 0.4953 | 0.6613 | 0.4944 |
| No log | 7.6667 | 46 | 0.4884 | 0.5689 | 0.4879 |
| No log | 8.0 | 48 | 0.4997 | 0.5052 | 0.4999 |
| No log | 8.3333 | 50 | 0.5187 | 0.4731 | 0.5194 |
| No log | 8.6667 | 52 | 0.5092 | 0.4731 | 0.5095 |
| No log | 9.0 | 54 | 0.4978 | 0.5052 | 0.4977 |
| No log | 9.3333 | 56 | 0.4999 | 0.5052 | 0.5000 |
| No log | 9.6667 | 58 | 0.5004 | 0.5052 | 0.5006 |
| No log | 10.0 | 60 | 0.4983 | 0.5052 | 0.4984 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|