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ROBERTA_Tweet_Sentiment_50k_2eps
joe5campbell/ROBERTA_Tweet_Sentiment_50k_2eps
ROBERTA_Tweet_Sentiment_50k_2eps is a text classification model from joe5campbell. Use it when you need a label for a piece of text. It is set up for transformers.
probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 21, 2022
- SHA
- 475ffb09
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
ROBERTA_Tweet_Sentiment_50k_2eps
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:
- Train Loss: 0.3553
- Train Accuracy: 0.8504
- Validation Loss: 0.5272
- Validation Accuracy: 0.7652
- Epoch: 1
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:
- optimizer: {'name': 'Adam', 'clipnorm': 1.0, 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.5213 | 0.7298 | 0.4817 | 0.7715 | 0 |
| 0.3553 | 0.8504 | 0.5272 | 0.7652 | 1 |
Framework versions
- Transformers 4.16.2
- TensorFlow 2.8.0
- Tokenizers 0.11.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2022
- Updated
- Feb 21, 2022