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finetune-bert-sentiment-analysis
aakinlalu/finetune-bert-sentiment-analysis
finetune-bert-sentiment-analysis is a text classification model from aakinlalu. 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
- Oct 28, 2024
- Updated
- Oct 28, 2024
- SHA
- d9f8cb1e
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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. -->
finetune-bert-sentiment-analysis
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2378
- Accuracy: 0.94
- F1score: 0.9455
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1score |
|---|---|---|---|---|---|
| 0.5361 | 1.0 | 100 | 0.4738 | 0.865 | 0.8811 |
| 0.1125 | 2.0 | 200 | 0.2378 | 0.94 | 0.9455 |
| 0.0357 | 3.0 | 300 | 0.2857 | 0.945 | 0.9507 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Oct 28, 2024
- Updated
- Oct 28, 2024