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my_test_model
NarmathaV/my_test_model
my_test_model is a text classification model from NarmathaV. 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
- Jun 4, 2025
- Updated
- Jun 25, 2025
- SHA
- 32b0663d
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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. -->
my_test_model
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: 1.2097
- Accuracy: 0.5209
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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6541 | 1.0 | 3044 | 1.0627 | 0.5209 |
| 0.6093 | 2.0 | 6088 | 1.2023 | 0.5209 |
| 0.5841 | 3.0 | 9132 | 1.2097 | 0.5209 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.8.0.dev20250318
- Datasets 3.3.2
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jun 4, 2025
- Updated
- Jun 25, 2025