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bert-sentiment-analysis
muralik0115/bert-sentiment-analysis
bert-sentiment-analysis is a text classification model from muralik0115. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- May 27, 2024
- Updated
- May 28, 2024
- SHA
- 6cf3f8dc
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Base models
Datasets
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. -->
bert-sentiment-analysis
This model is a fine-tuned version of google-bert/bert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1285
- Accuracy: 0.946
- F1: 0.9458
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: 24
- eval_batch_size: 24
- 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 | F1 |
|---|---|---|---|---|---|
| 0.4104 | 1.0 | 667 | 0.1901 | 0.93 | 0.9306 |
| 0.1271 | 2.0 | 1334 | 0.1207 | 0.94 | 0.9391 |
| 0.0832 | 3.0 | 2001 | 0.1285 | 0.946 | 0.9458 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 27, 2024
- Updated
- May 28, 2024