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finetuning-sentiment-analysis-siebert
aruca/finetuning-sentiment-analysis-siebert
finetuning-sentiment-analysis-siebert is a text classification model from aruca. 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
- Jan 16, 2024
- Updated
- Jan 16, 2024
- SHA
- e100335c
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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. -->
finetuning-sentiment-analysis-siebert
This model is a fine-tuned version of siebert/sentiment-roberta-large-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2571
- Accuracy: 0.7929
- F1: [0.79305355 0.75473045 0.8413856 ]
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 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jan 16, 2024
- Updated
- Jan 16, 2024