metadata
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model4_arabertv2_base_T2_WS_A100
results: []
Model4_arabertv2_base_T2_WS_A100
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02-twitter on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0654
- F1: 0.8501
- Roc Auc: 0.9178
- Accuracy: 0.7616
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: 5e-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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 193 | 0.1020 | 0.7502 | 0.8274 | 0.6443 |
| No log | 2.0 | 386 | 0.0759 | 0.8068 | 0.8678 | 0.7114 |
| 0.1069 | 3.0 | 579 | 0.0728 | 0.8240 | 0.8890 | 0.7393 |
| 0.1069 | 4.0 | 772 | 0.0670 | 0.8418 | 0.9112 | 0.7635 |
| 0.1069 | 5.0 | 965 | 0.0654 | 0.8501 | 0.9178 | 0.7616 |
| 0.0318 | 6.0 | 1158 | 0.0669 | 0.8467 | 0.9197 | 0.7579 |
| 0.0318 | 7.0 | 1351 | 0.0686 | 0.8471 | 0.9190 | 0.7672 |
| 0.0141 | 8.0 | 1544 | 0.0705 | 0.8493 | 0.9259 | 0.7561 |
| 0.0141 | 9.0 | 1737 | 0.0732 | 0.8450 | 0.9248 | 0.7486 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3