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fine-tuned-arabert-random-negative9-1
aomar85/fine-tuned-arabert-random-negative9-1
fine-tuned-arabert-random-negative9-1 is a text classification model from aomar85. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jun 2, 2022
- Updated
- Jun 5, 2022
- SHA
- 3802124a
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Model card
From the Hugging Face model README
<!-- 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. -->
fine-tuned-arabert-random-negative9-1
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0070
- Accuracy: 0.9989
- Precision: 0.9995
- Recall: 0.9993
- F1: 0.9994
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.024 | 1.0 | 34360 | 0.0069 | 0.9988 | 0.9989 | 0.9998 | 0.9993 |
| 0.0175 | 2.0 | 68720 | 0.0096 | 0.9989 | 0.9993 | 0.9994 | 0.9994 |
| 0.015 | 3.0 | 103080 | 0.0102 | 0.9987 | 0.9996 | 0.9990 | 0.9993 |
| 0.014 | 4.0 | 137440 | 0.0070 | 0.9989 | 0.9995 | 0.9993 | 0.9994 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Jun 2, 2022
- Updated
- Jun 5, 2022