File size: 2,184 Bytes
03e5443 |
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 |
---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fold_4
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. -->
# fold_4
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4181
- Accuracy: 0.8452
- Macro F1: 0.8447
- Weighted F1: 0.8452
- F1 Pro: 0.8421
- F1 Against: 0.8571
- F1 Neutral: 0.8350
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:|
| 0.8777 | 1.1628 | 50 | 0.5462 | 0.8095 | 0.8101 | 0.8102 | 0.8468 | 0.7874 | 0.7959 |
| 0.4709 | 2.3256 | 100 | 0.4626 | 0.8274 | 0.8277 | 0.8275 | 0.8571 | 0.8034 | 0.8224 |
| 0.27 | 3.4884 | 150 | 0.4181 | 0.8452 | 0.8447 | 0.8452 | 0.8421 | 0.8571 | 0.8350 |
| 0.2101 | 4.6512 | 200 | 0.5017 | 0.8095 | 0.8088 | 0.8094 | 0.8421 | 0.8 | 0.7843 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
|