metadata
base_model: aubmindlab/bert-base-arabertv02-twitter
tags:
- generated_from_trainer
datasets:
- ajgt_twitter_ar
metrics:
- accuracy
model-index:
- name: Testmeee
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ajgt_twitter_ar
type: ajgt_twitter_ar
config: plain_text
split: train
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.95
Testmeee
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02-twitter on the ajgt_twitter_ar dataset. It achieves the following results on the evaluation set:
- Loss: 0.3318
- Accuracy: 0.95
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Accuracy |
|---|---|---|---|---|
| 0.4258 | 1.11 | 50 | 0.2875 | 0.88 |
| 0.1848 | 2.22 | 100 | 0.2274 | 0.93 |
| 0.1117 | 3.33 | 150 | 0.2743 | 0.9 |
| 0.0598 | 4.44 | 200 | 0.2292 | 0.94 |
| 0.0354 | 5.56 | 250 | 0.2714 | 0.95 |
| 0.0319 | 6.67 | 300 | 0.2870 | 0.95 |
| 0.0195 | 7.78 | 350 | 0.3029 | 0.95 |
| 0.0136 | 8.89 | 400 | 0.3097 | 0.95 |
| 0.0078 | 10.0 | 450 | 0.3197 | 0.95 |
| 0.0088 | 11.11 | 500 | 0.3227 | 0.95 |
| 0.0057 | 12.22 | 550 | 0.3263 | 0.95 |
| 0.0058 | 13.33 | 600 | 0.3283 | 0.95 |
| 0.0051 | 14.44 | 650 | 0.3318 | 0.95 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1