Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use PepperMintButler/GyoMail with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PepperMintButler/GyoMail with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PepperMintButler/GyoMail")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PepperMintButler/GyoMail") model = AutoModelForSequenceClassification.from_pretrained("PepperMintButler/GyoMail", device_map="auto") - Notebooks
- Google Colab
- Kaggle
GyoMail
This model is a fine-tuned version of distilroberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0612
- Accuracy: 0.9927
- Precision: 0.9965
- Recall: 0.9892
- F1: 0.9928
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: 128
- 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0794 | 1.0 | 974 | 0.0508 | 0.9923 | 0.9960 | 0.9890 | 0.9924 |
| 0.0336 | 2.0 | 1948 | 0.0612 | 0.9927 | 0.9965 | 0.9892 | 0.9928 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.23.1
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Model tree for PepperMintButler/GyoMail
Base model
distilbert/distilroberta-base