Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use xcbhuiii/distilbert-imdb-sentiment-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xcbhuiii/distilbert-imdb-sentiment-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xcbhuiii/distilbert-imdb-sentiment-demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xcbhuiii/distilbert-imdb-sentiment-demo") model = AutoModelForSequenceClassification.from_pretrained("xcbhuiii/distilbert-imdb-sentiment-demo") - Notebooks
- Google Colab
- Kaggle
distilbert-imdb-sentiment-demo
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
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: 32
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0020 | 0.4 | 100 | 0.0010 | 1.0 |
| 0.0005 | 0.8 | 200 | 0.0003 | 1.0 |
| 0.0002 | 1.2 | 300 | 0.0002 | 1.0 |
| 0.0001 | 1.6 | 400 | 0.0001 | 1.0 |
| 0.0001 | 2.0 | 500 | 0.0001 | 1.0 |
| 0.0001 | 2.4 | 600 | 0.0000 | 1.0 |
| 0.0001 | 2.8 | 700 | 0.0000 | 1.0 |
| 0.0000 | 3.2 | 800 | 0.0000 | 1.0 |
| 0.0000 | 3.6 | 900 | 0.0000 | 1.0 |
| 0.0000 | 4.0 | 1000 | 0.0000 | 1.0 |
| 0.0000 | 4.4 | 1100 | 0.0000 | 1.0 |
| 0.0000 | 4.8 | 1200 | 0.0000 | 1.0 |
| 0.0000 | 5.0 | 1250 | 0.0000 | 1.0 |
Framework versions
- Transformers 5.4.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
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Model tree for xcbhuiii/distilbert-imdb-sentiment-demo
Base model
distilbert/distilbert-base-uncased