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roberta-base-finetuned-swag
Payoto/roberta-base-finetuned-swag
roberta-base-finetuned-swag is a machine learning model from Payoto. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Nov 14, 2022
- Updated
- Dec 18, 2022
- SHA
- 77935bed
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-base-finetuned-swag
This model is a fine-tuned version of roberta-base on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.4382
- Accuracy: 0.8390
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- training precision: Mixed Precision
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5707 | 1.0 | 574 | 0.4990 | 0.8097 |
| 0.5092 | 2.0 | 1148 | 0.4321 | 0.8361 |
| 0.3597 | 3.0 | 1722 | 0.4382 | 0.8390 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.0+cpu
- Datasets 2.7.1
- Tokenizers 0.12.1
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Nov 14, 2022
- Updated
- Dec 18, 2022