File size: 1,992 Bytes
e961484 |
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 |
---
base_model: SI2M-Lab/DarijaBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
model-index:
- name: results
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. -->
# results
This model is a fine-tuned version of [SI2M-Lab/DarijaBERT](https://huggingface.co/SI2M-Lab/DarijaBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5291
- Macro F1: 0.7697
- Accuracy: 0.8007
- Recall: 0.7687
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 | Macro F1 | Accuracy | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:------:|
| 0.6848 | 0.9877 | 40 | 0.6040 | 0.6869 | 0.7504 | 0.6821 |
| 0.5937 | 2.0 | 81 | 0.5376 | 0.7396 | 0.7799 | 0.7286 |
| 0.4946 | 2.9877 | 121 | 0.5313 | 0.7474 | 0.7816 | 0.7434 |
| 0.386 | 4.0 | 162 | 0.5291 | 0.7697 | 0.8007 | 0.7687 |
| 0.3114 | 4.9877 | 202 | 0.5690 | 0.7391 | 0.7782 | 0.7329 |
| 0.2477 | 6.0 | 243 | 0.5891 | 0.7480 | 0.7834 | 0.7441 |
| 0.1804 | 6.9877 | 283 | 0.6194 | 0.7422 | 0.7764 | 0.7366 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|