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covid-tweet-sentimental-Analysis-roberta
gyesibiney/covid-tweet-sentimental-Analysis-roberta
covid-tweet-sentimental-Analysis-roberta 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Jul 13, 2023
- Updated
- Sep 1, 2023
- SHA
- 1d629c43
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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. -->
test_trainer
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6957
- Accuracy: 0.7107
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: 8
- eval_batch_size: 8
- seed: 42
- 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 |
|---|---|---|---|---|
| 0.8279 | 0.52 | 500 | 0.8843 | 0.6755 |
| 0.7718 | 1.04 | 1000 | 0.7864 | 0.6786 |
| 0.739 | 1.55 | 1500 | 0.7484 | 0.6982 |
| 0.7014 | 2.07 | 2000 | 0.7300 | 0.7039 |
| 0.6634 | 2.59 | 2500 | 0.6957 | 0.7107 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jul 13, 2023
- Updated
- Sep 1, 2023