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bert-base-uncased_finetuning_distillation
ashabrawy/bert-base-uncased_finetuning_distillation
bert-base-uncased_finetuning_distillation is a text classification model from ashabrawy. 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
- Mar 14, 2024
- Updated
- Mar 14, 2024
- SHA
- b5889f3e
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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. -->
bert-base-uncased_finetuning_distillation
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4298
- Accuracy: 0.8332
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5966 | 1.39 | 500 | 0.7974 | 0.6719 |
| 0.5528 | 2.78 | 1000 | 0.5465 | 0.7900 |
| 0.2857 | 4.17 | 1500 | 0.4594 | 0.8264 |
| 0.1546 | 5.56 | 2000 | 0.4235 | 0.8401 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 14, 2024
- Updated
- Mar 14, 2024