File size: 3,311 Bytes
839d778 |
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 |
---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_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_cross_relevance_task1_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: 0.1989
- Qwk: 0.0319
- Mse: 0.1989
## 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 | 0.0351 | 2 | 0.4878 | 0.0163 | 0.4878 |
| No log | 0.0702 | 4 | 0.1886 | 0.0202 | 0.1886 |
| No log | 0.1053 | 6 | 0.1831 | 0.0185 | 0.1831 |
| No log | 0.1404 | 8 | 0.2686 | 0.0273 | 0.2686 |
| No log | 0.1754 | 10 | 0.2485 | 0.0273 | 0.2485 |
| No log | 0.2105 | 12 | 0.2552 | 0.0273 | 0.2552 |
| No log | 0.2456 | 14 | 0.2716 | 0.0254 | 0.2716 |
| No log | 0.2807 | 16 | 0.3347 | 0.0217 | 0.3347 |
| No log | 0.3158 | 18 | 0.3725 | 0.0323 | 0.3725 |
| No log | 0.3509 | 20 | 0.3182 | 0.0361 | 0.3182 |
| No log | 0.3860 | 22 | 0.2412 | 0.0319 | 0.2412 |
| No log | 0.4211 | 24 | 0.1936 | 0.0319 | 0.1936 |
| No log | 0.4561 | 26 | 0.1659 | 0.0319 | 0.1659 |
| No log | 0.4912 | 28 | 0.1540 | 0.0339 | 0.1540 |
| No log | 0.5263 | 30 | 0.1483 | 0.0254 | 0.1483 |
| No log | 0.5614 | 32 | 0.1525 | 0.0273 | 0.1525 |
| No log | 0.5965 | 34 | 0.1560 | 0.0359 | 0.1560 |
| No log | 0.6316 | 36 | 0.1603 | 0.0339 | 0.1603 |
| No log | 0.6667 | 38 | 0.1720 | 0.0319 | 0.1720 |
| No log | 0.7018 | 40 | 0.1847 | 0.0319 | 0.1847 |
| No log | 0.7368 | 42 | 0.2033 | 0.0319 | 0.2033 |
| No log | 0.7719 | 44 | 0.2175 | 0.0319 | 0.2175 |
| No log | 0.8070 | 46 | 0.2213 | 0.0319 | 0.2213 |
| No log | 0.8421 | 48 | 0.2184 | 0.0319 | 0.2184 |
| No log | 0.8772 | 50 | 0.2126 | 0.0319 | 0.2126 |
| No log | 0.9123 | 52 | 0.2064 | 0.0319 | 0.2064 |
| No log | 0.9474 | 54 | 0.2016 | 0.0319 | 0.2016 |
| No log | 0.9825 | 56 | 0.1989 | 0.0319 | 0.1989 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|