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distilbert-tweet-sentiment-finetuned
Siddharth466/distilbert-tweet-sentiment-finetuned
distilbert-tweet-sentiment-finetuned is a text classification model from Siddharth466. 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
- distilbert
- Access
- Public
- Created
- Feb 20, 2026
- Updated
- Feb 24, 2026
- SHA
- 330adbb7
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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. -->
distilbert-tweet-sentiment
This model is a fine-tuned version of distilbert-base-uncased on tweets dataset to perform sentiment classification. It achieves the following results on the evaluation set:
- Loss: 0.6587
- Accuracy: 0.7404
- F1: 0.6988
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6192 | 1.0 | 2851 | 0.6211 | 0.734 | 0.7332 |
| 0.4953 | 2.0 | 5702 | 0.6309 | 0.7445 | 0.7417 |
| 0.3723 | 3.0 | 8553 | 0.6922 | 0.734 | 0.7333 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 20, 2026
- Updated
- Feb 24, 2026