Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use 53gf4u1t/XCommentsClassificationModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 53gf4u1t/XCommentsClassificationModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="53gf4u1t/XCommentsClassificationModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("53gf4u1t/XCommentsClassificationModel") model = AutoModelForSequenceClassification.from_pretrained("53gf4u1t/XCommentsClassificationModel") - Notebooks
- Google Colab
- Kaggle
XCommentsClassificationModel
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2281
- Accuracy: 0.9286
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: 64
- eval_batch_size: 64
- 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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4929 | 5.0 | 20 | 0.4759 | 0.8929 |
| 0.1498 | 10.0 | 40 | 0.2220 | 0.8929 |
| 0.0244 | 15.0 | 60 | 0.1492 | 0.9286 |
| 0.0103 | 20.0 | 80 | 0.1755 | 0.9286 |
| 0.0069 | 25.0 | 100 | 0.2381 | 0.9286 |
| 0.0052 | 30.0 | 120 | 0.1952 | 0.9286 |
| 0.0047 | 35.0 | 140 | 0.2168 | 0.9286 |
| 0.004 | 40.0 | 160 | 0.2249 | 0.9286 |
| 0.004 | 45.0 | 180 | 0.2260 | 0.9286 |
| 0.0038 | 50.0 | 200 | 0.2281 | 0.9286 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
- Downloads last month
- 2
Model tree for 53gf4u1t/XCommentsClassificationModel
Base model
distilbert/distilbert-base-uncased