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roberta-base-trans-finetuned-mnli
aabid123/roberta-base-trans-finetuned-mnli
roberta-base-trans-finetuned-mnli is a text classification model from aabid123. 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
- May 3, 2024
- Updated
- May 3, 2024
- SHA
- 7630b829
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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. -->
roberta-base-trans-finetuned-mnli
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3457
- Accuracy: 0.7854
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 |
|---|---|---|---|---|
| No log | 1.0 | 487 | 0.3958 | 0.7485 |
| 0.5754 | 2.0 | 974 | 0.3381 | 0.7834 |
| 0.3974 | 3.0 | 1461 | 0.3698 | 0.7485 |
| 0.3422 | 4.0 | 1948 | 0.3504 | 0.7454 |
| 0.3237 | 5.0 | 2435 | 0.3457 | 0.7854 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- May 3, 2024
- Updated
- May 3, 2024