metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: answerdotai-ModernBERT-base-finetuned
results: []
answerdotai-ModernBERT-base-finetuned
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: 0.0116
- Accuracy: 0.9976
- Precision: 0.9977
- Recall: 0.9976
- F1: 0.9976
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: 4.244005797262286e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0175 | 1.0 | 1506 | 0.0195 | 0.9971 | 0.9971 | 0.9971 | 0.9971 |
| 0.0134 | 2.0 | 3012 | 0.0153 | 0.9970 | 0.9970 | 0.9970 | 0.9970 |
| 0.0 | 3.0 | 4518 | 0.0228 | 0.9976 | 0.9976 | 0.9976 | 0.9976 |
| 0.0 | 4.0 | 6024 | 0.0270 | 0.9976 | 0.9976 | 0.9976 | 0.9976 |
| 0.0 | 5.0 | 7530 | 0.0272 | 0.9976 | 0.9976 | 0.9976 | 0.9976 |
| 0.0 | 6.0 | 9036 | 0.0279 | 0.9975 | 0.9975 | 0.9975 | 0.9975 |
| 0.0 | 7.0 | 10542 | 0.0283 | 0.9975 | 0.9975 | 0.9975 | 0.9975 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0