File size: 3,460 Bytes
7d8168d ee04769 7d8168d ee04769 7d8168d ee04769 7d8168d ee04769 7d8168d |
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_vocabulary_task7_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_vocabulary_task7_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: 0.4434
- Qwk: 0.7306
- Mse: 0.4409
## 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 | 1.1716 | 0.2597 | 1.1767 |
| No log | 0.6667 | 4 | 0.7370 | 0.5706 | 0.7641 |
| No log | 1.0 | 6 | 0.7497 | 0.5562 | 0.7703 |
| No log | 1.3333 | 8 | 0.6581 | 0.5987 | 0.6708 |
| No log | 1.6667 | 10 | 0.6557 | 0.4 | 0.6660 |
| No log | 2.0 | 12 | 0.4981 | 0.7242 | 0.5095 |
| No log | 2.3333 | 14 | 0.5966 | 0.5490 | 0.6027 |
| No log | 2.6667 | 16 | 0.7334 | 0.5273 | 0.7340 |
| No log | 3.0 | 18 | 0.7026 | 0.5268 | 0.7001 |
| No log | 3.3333 | 20 | 0.5537 | 0.6360 | 0.5517 |
| No log | 3.6667 | 22 | 0.5745 | 0.6402 | 0.5704 |
| No log | 4.0 | 24 | 0.6711 | 0.5418 | 0.6622 |
| No log | 4.3333 | 26 | 0.6481 | 0.5418 | 0.6370 |
| No log | 4.6667 | 28 | 0.5399 | 0.6015 | 0.5315 |
| No log | 5.0 | 30 | 0.4583 | 0.6890 | 0.4538 |
| No log | 5.3333 | 32 | 0.4300 | 0.7379 | 0.4272 |
| No log | 5.6667 | 34 | 0.4490 | 0.6402 | 0.4450 |
| No log | 6.0 | 36 | 0.5299 | 0.6360 | 0.5222 |
| No log | 6.3333 | 38 | 0.5460 | 0.5268 | 0.5387 |
| No log | 6.6667 | 40 | 0.4926 | 0.6360 | 0.4893 |
| No log | 7.0 | 42 | 0.4501 | 0.6402 | 0.4494 |
| No log | 7.3333 | 44 | 0.4428 | 0.7379 | 0.4421 |
| No log | 7.6667 | 46 | 0.4707 | 0.6360 | 0.4684 |
| No log | 8.0 | 48 | 0.4833 | 0.6360 | 0.4804 |
| No log | 8.3333 | 50 | 0.5033 | 0.6360 | 0.4988 |
| No log | 8.6667 | 52 | 0.5001 | 0.6360 | 0.4953 |
| No log | 9.0 | 54 | 0.4748 | 0.6833 | 0.4711 |
| No log | 9.3333 | 56 | 0.4541 | 0.6833 | 0.4512 |
| No log | 9.6667 | 58 | 0.4462 | 0.6833 | 0.4437 |
| No log | 10.0 | 60 | 0.4434 | 0.7306 | 0.4409 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|