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distilroberta-base-mrpc-glue-keith-alec
aleckeithc/distilroberta-base-mrpc-glue-keith-alec
distilroberta-base-mrpc-glue-keith-alec is a text classification model from aleckeithc. 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
- roberta
- Access
- Public
- Created
- Dec 4, 2023
- Updated
- Dec 4, 2023
- SHA
- dfc3051f
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Datasets
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. -->
distilroberta-base-mrpc-glue-keith-alec
This model is a fine-tuned version of distilroberta-base on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
- Loss: 0.6392
- Accuracy: 0.8529
- F1: 0.8958
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: 8
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3596 | 1.09 | 500 | 1.1183 | 0.8309 | 0.8848 |
| 0.3241 | 2.18 | 1000 | 0.6392 | 0.8529 | 0.8958 |
| 0.1673 | 3.27 | 1500 | 0.7843 | 0.8431 | 0.8869 |
| 0.0807 | 4.36 | 2000 | 0.9659 | 0.8456 | 0.8916 |
Framework versions
- Transformers 4.29.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Dec 4, 2023
- Updated
- Dec 4, 2023