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distilbert-base-uncased-finetuned-qnli
Dyuxiang/distilbert-base-uncased-finetuned-qnli
distilbert-base-uncased-finetuned-qnli is a machine learning model from Dyuxiang. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 8, 2024
- Updated
- Aug 8, 2024
- SHA
- cefe69be
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. -->
distilbert-base-uncased-finetuned-qnli
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: 0.4778
- Accuracy: 0.8949
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3466 | 1.0 | 6547 | 0.2966 | 0.8823 |
| 0.264 | 2.0 | 13094 | 0.3132 | 0.8777 |
| 0.2057 | 3.0 | 19641 | 0.3581 | 0.8893 |
| 0.136 | 4.0 | 26188 | 0.4778 | 0.8949 |
| 0.0898 | 5.0 | 32735 | 0.5774 | 0.8904 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu118
- Datasets 2.19.2
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 8, 2024
- Updated
- Aug 8, 2024