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Model4_arabertv2_base_T2_WS_A100
SMG0/Model4_arabertv2_base_T2_WS_A100
Model4_arabertv2_base_T2_WS_A100 is a text classification model from SMG0. 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
- Aug 15, 2023
- Updated
- Aug 15, 2023
- SHA
- c50eb0bb
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Base models
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. -->
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: 0.0694
- F1: 0.8430
- Roc Auc: 0.9128
- Accuracy: 0.7523
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 | 0.0694 | 0.8430 | 0.9128 | 0.7523 |
| No log | 2.0 | 386 | 0.0713 | 0.8489 | 0.9184 | 0.7598 |
| 0.0183 | 3.0 | 579 | 0.0779 | 0.8377 | 0.9226 | 0.7412 |
| 0.0183 | 4.0 | 772 | 0.0727 | 0.8455 | 0.9181 | 0.7523 |
| 0.0183 | 5.0 | 965 | 0.0749 | 0.8555 | 0.9264 | 0.7672 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Aug 15, 2023
- Updated
- Aug 15, 2023