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roberta-large-bn-adapter-3.17M-snli-model2
varun-v-rao/roberta-large-bn-adapter-3.17M-snli-model2
roberta-large-bn-adapter-3.17M-snli-model2 is a machine learning model from varun-v-rao. 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 mit.
should probably proofread and complete it, then remove this comment. --
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Updated Feb 7, 2024
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At a glance
- License
- mit
- Access
- Public
- Created
- Feb 7, 2024
- Updated
- Feb 7, 2024
- SHA
- 63e5f486
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-large-bn-adapter-3.17M-snli-model2
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6172
- Accuracy: 0.8015
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: 64
- eval_batch_size: 64
- seed: 27
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3134 | 1.0 | 8584 | 0.2371 | 0.9160 |
| 0.2891 | 2.0 | 17168 | 0.2228 | 0.9224 |
| 0.2792 | 3.0 | 25752 | 0.2222 | 0.9237 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- mit
- Created
- Feb 7, 2024
- Updated
- Feb 7, 2024