Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use justmeomeo1/distilbert-base-uncased-finetuned-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use justmeomeo1/distilbert-base-uncased-finetuned-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="justmeomeo1/distilbert-base-uncased-finetuned-clinc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("justmeomeo1/distilbert-base-uncased-finetuned-clinc") model = AutoModelForSequenceClassification.from_pretrained("justmeomeo1/distilbert-base-uncased-finetuned-clinc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
distilbert-base-uncased-finetuned-clinc
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: 0.7937
- Accuracy: 0.9184
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: 48
- eval_batch_size: 48
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.2976 | 0.7271 |
| 3.8004 | 2.0 | 636 | 1.8844 | 0.8432 |
| 3.8004 | 3.0 | 954 | 1.1731 | 0.8887 |
| 1.7125 | 4.0 | 1272 | 0.8779 | 0.9132 |
| 0.9194 | 5.0 | 1590 | 0.7937 | 0.9184 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.10.0+cu126
- Datasets 4.8.4
- Tokenizers 0.22.2
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Model tree for justmeomeo1/distilbert-base-uncased-finetuned-clinc
Base model
distilbert/distilbert-base-uncased