Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use Tharun124/Helpdeskemail-ModernBERT-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tharun124/Helpdeskemail-ModernBERT-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tharun124/Helpdeskemail-ModernBERT-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tharun124/Helpdeskemail-ModernBERT-classifier") model = AutoModelForSequenceClassification.from_pretrained("Tharun124/Helpdeskemail-ModernBERT-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Helpdeskemail-ModernBERT-classifier
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3753
- Accuracy: 0.4118
- F1 Macro: 0.2364
- Precision Macro: 0.2178
- Recall Macro: 0.2667
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: 16
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|
| 1.5053 | 1.0 | 9 | 1.3558 | 0.375 | 0.1091 | 0.075 | 0.2 |
| 1.3372 | 2.0 | 18 | 1.2194 | 0.5625 | 0.3301 | 0.4091 | 0.3467 |
| 0.9994 | 3.0 | 27 | 1.1430 | 0.625 | 0.3691 | 0.4333 | 0.3867 |
| 0.8771 | 4.0 | 36 | 1.0844 | 0.625 | 0.3743 | 0.4133 | 0.4133 |
| 0.6594 | 5.0 | 45 | 1.0345 | 0.6875 | 0.4243 | 0.4333 | 0.4533 |
Framework versions
- Transformers 5.6.2
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
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Model tree for Tharun124/Helpdeskemail-ModernBERT-classifier
Base model
answerdotai/ModernBERT-base