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roberta-large-mnli-fer-finetuned
vish88/roberta-large-mnli-fer-finetuned
roberta-large-mnli-fer-finetuned is a text classification model from vish88. 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
- Jul 15, 2022
- Updated
- Jul 22, 2022
- SHA
- 0c7894ea
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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-mnli-fer-finetuned
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6940
- Accuracy: 0.5005
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.7049 | 1.0 | 554 | 0.6895 | 0.5750 |
| 0.6981 | 2.0 | 1108 | 0.7054 | 0.5005 |
| 0.7039 | 3.0 | 1662 | 0.6936 | 0.5005 |
| 0.6976 | 4.0 | 2216 | 0.6935 | 0.4995 |
| 0.6991 | 5.0 | 2770 | 0.6940 | 0.5005 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jul 15, 2022
- Updated
- Jul 22, 2022