metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ModernBERT-domain-classifier
results: []
ModernBERT-domain-classifier
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.04
- F1: 0.0032
- F1 Weighted: 0.0031
- Precision: 0.0016
- Recall: 0.04
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: 5e-05
- train_batch_size: 32
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | F1 Weighted | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 29 | nan | 0.04 | 0.0032 | 0.0031 | 0.0016 | 0.04 |
| No log | 2.0 | 58 | nan | 0.04 | 0.0032 | 0.0031 | 0.0016 | 0.04 |
| No log | 3.0 | 87 | nan | 0.04 | 0.0032 | 0.0031 | 0.0016 | 0.04 |
| 0.0 | 4.0 | 116 | nan | 0.04 | 0.0032 | 0.0031 | 0.0016 | 0.04 |
| 0.0 | 5.0 | 145 | nan | 0.04 | 0.0032 | 0.0031 | 0.0016 | 0.04 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.0+cu124
- Datasets 3.1.0
- Tokenizers 0.21.2