My Sentiment Model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
Model source
- Kind
- Other
- File size
- 255 MB
- Base model
- distilbert-base-uncased
- Version
- vRevision 9ab2384
- Updated
- Nov 4, 2026
- Publisher
- @rislrohitjain
- Downloads
- 3
- Source
- Hugging Face
Source description
my-sentiment-model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
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_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
Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cpu
- Datasets 4.8.5
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Nov 4
Download files
Repository files
File inventory only; completeness is unverified.
Model artifacts
1 artifact
Model artifacts
1 artifactmodel.safetensors
safetensors · FP32 (tensor header) · 255 MB · SHA-256 dcbf49797b34…c37f · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- library_name: transformers license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer model-index: - name: my-sentiment-model results: [] --- <!-- 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-sentiment-model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. ## 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_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 ### Framework versions - Transformers 5.9.0 - Pytorch 2.12.0+cpu - Datasets 4.8.5 - Tokenizers 0.22.2
Source context: 3 downloads · 0 likes · Pipeline text-classification · Library transformers · Repo rislrohitjain/my-sentiment-model
Source context: 1 downloads · 0 likes · Pipeline text-classification · Library transformers · Repo rislrohitjain/my-sentiment-model
