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distil-bert-fine-tuned-boolq-v2
rycecorn/distil-bert-fine-tuned-boolq-v2
distil-bert-fine-tuned-boolq-v2 is a text classification model from rycecorn. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- May 28, 2024
- Updated
- May 28, 2024
- SHA
- 9c65b4da
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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. -->
distil-bert-fine-tuned-boolq-v2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4708
- Accuracy: 0.7269
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6018 | 1.0 | 2357 | 0.6215 | 0.6801 |
| 0.5588 | 2.0 | 4714 | 0.6642 | 0.7107 |
| 0.4521 | 3.0 | 7071 | 0.9947 | 0.7138 |
| 0.3341 | 4.0 | 9428 | 1.3616 | 0.7315 |
| 0.2011 | 5.0 | 11785 | 1.4708 | 0.7269 |
Framework versions
- Transformers 4.39.3
- Pytorch 1.13.0
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- May 28, 2024
- Updated
- May 28, 2024