metadata
base_model: SI2M-Lab/DarijaBERT-arabizi
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-DarijaBERT-arabizi
results: []
ner-DarijaBERT-arabizi
This model is a fine-tuned version of SI2M-Lab/DarijaBERT-arabizi on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1011
- Precision: 0.7475
- Recall: 0.7753
- F1: 0.7611
- Accuracy: 0.9681
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: 64
- eval_batch_size: 64
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 32 | 0.3240 | 0.5397 | 0.3251 | 0.4058 | 0.8996 |
| No log | 2.0 | 64 | 0.2541 | 0.5593 | 0.4720 | 0.5120 | 0.9203 |
| No log | 3.0 | 96 | 0.2062 | 0.5697 | 0.5828 | 0.5762 | 0.9350 |
| No log | 4.0 | 128 | 0.1791 | 0.6162 | 0.6313 | 0.6236 | 0.9426 |
| No log | 5.0 | 160 | 0.1528 | 0.6504 | 0.6803 | 0.6650 | 0.9509 |
| No log | 6.0 | 192 | 0.1308 | 0.6880 | 0.7262 | 0.7066 | 0.9582 |
| No log | 7.0 | 224 | 0.1189 | 0.7126 | 0.7270 | 0.7198 | 0.9612 |
| No log | 8.0 | 256 | 0.1100 | 0.7307 | 0.7661 | 0.7480 | 0.9651 |
| No log | 9.0 | 288 | 0.1037 | 0.7423 | 0.7567 | 0.7494 | 0.9667 |
| No log | 10.0 | 320 | 0.1011 | 0.7475 | 0.7753 | 0.7611 | 0.9681 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0