metadata
base_model: aubmindlab/bert-large-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: arabert-sentiment-classification
results: []
arabert-sentiment-classification
This model is a fine-tuned version of aubmindlab/bert-large-arabertv2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6123
- Macro F1: 0.6539
- Accuracy: 0.7723
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: 128
- seed: 25
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
|---|---|---|---|---|---|
| No log | 1.0 | 491 | 0.6646 | 0.5748 | 0.7527 |
| 0.9023 | 2.0 | 983 | 0.6157 | 0.6093 | 0.7710 |
| 0.6187 | 3.0 | 1473 | 0.6123 | 0.6539 | 0.7723 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.14.1