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roberta-large-finetuned-mnli-batch_size_4_100000_samples
Kuaaangwen/roberta-large-finetuned-mnli-batch_size_4_100000_samples
roberta-large-finetuned-mnli-batch_size_4_100000_samples is a text classification model from Kuaaangwen. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Dec 6, 2022
- Updated
- Dec 6, 2022
- SHA
- bd5aadb8
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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. -->
roberta-large-finetuned-mnli-batch_size_4_100000_samples
This model is a fine-tuned version of roberta-large on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.0980
- Accuracy: 0.3545
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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1026 | 1.0 | 25000 | 1.0980 | 0.3545 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 6, 2022
- Updated
- Dec 6, 2022