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Sentiment-review-analysis-roberta-3
gyesibiney/Sentiment-review-analysis-roberta-3
Sentiment-review-analysis-roberta-3 is a text classification model from gyesibiney. 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
- Sep 8, 2023
- Updated
- Sep 10, 2023
- SHA
- 750a274a
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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-capstone_2
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3485
- Accuracy: 0.9400
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.2568 | 1.0 | 623 | 0.1971 | 0.9265 |
| 0.1581 | 2.0 | 1246 | 0.2102 | 0.9339 |
| 0.109 | 3.0 | 1869 | 0.3126 | 0.9356 |
| 0.0687 | 4.0 | 2492 | 0.3040 | 0.9382 |
| 0.0199 | 5.0 | 3115 | 0.3485 | 0.9400 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Sep 8, 2023
- Updated
- Sep 10, 2023