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finetuning-sentiment-model-deberta-smote
devtanumisra/finetuning-sentiment-model-deberta-smote
finetuning-sentiment-model-deberta-smote is a text classification model from devtanumisra. 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
- deberta-v2
- Access
- Public
- Created
- Nov 14, 2022
- Updated
- Nov 14, 2022
- SHA
- e0af5ad1
Try a prompt
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. -->
finetuning-sentiment-model-deberta-smote
This model is a fine-tuned version of yangheng/deberta-v3-base-absa-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4852
- Accuracy: 0.7215
- F1: 0.7215
- Precision: 0.7215
- Recall: 0.7215
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Nov 14, 2022
- Updated
- Nov 14, 2022