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chat-sentiment-finetuned-English
bottaz/chat-sentiment-finetuned-English
chat-sentiment-finetuned-English is a text classification model from bottaz. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 25, 2025
- Updated
- Aug 26, 2025
- SHA
- 5d04f3bd
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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. -->
chat-sentiment-finetuned-English
This model is a fine-tuned version of tabularisai/multilingual-sentiment-analysis on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8225
- Accuracy: 0.6932
- F1: 0.6947
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: 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 |
|---|---|---|---|---|---|
| No log | 1.0 | 89 | 0.9510 | 0.625 | 0.6122 |
| No log | 2.0 | 178 | 0.8132 | 0.6932 | 0.6970 |
| No log | 3.0 | 267 | 0.8225 | 0.6932 | 0.6947 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- cc-by-nc-4.0
- Created
- Aug 25, 2025
- Updated
- Aug 26, 2025