---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# results

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2000
- Accuracy: 0.9433
- F1: 0.9429
- Precision: 0.9508
- Recall: 0.9433

## 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: 4e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- 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 | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 3.8028        | 0.0833 | 25   | 1.5191          | 0.3944   | 0.2893 | 0.4598    | 0.3944 |
| 2.2046        | 0.1667 | 50   | 0.7147          | 0.75     | 0.7423 | 0.7685    | 0.75   |
| 1.2172        | 0.25   | 75   | 0.6074          | 0.7989   | 0.7727 | 0.8508    | 0.7989 |
| 0.9054        | 0.3333 | 100  | 0.3817          | 0.8656   | 0.8637 | 0.8907    | 0.8656 |
| 0.873         | 0.4167 | 125  | 0.3460          | 0.8678   | 0.8665 | 0.8810    | 0.8678 |
| 0.7074        | 0.5    | 150  | 0.2918          | 0.8889   | 0.8848 | 0.9159    | 0.8889 |
| 1.0552        | 0.5833 | 175  | 0.2550          | 0.89     | 0.8868 | 0.9130    | 0.89   |
| 0.5167        | 0.6667 | 200  | 0.2660          | 0.9044   | 0.9043 | 0.9071    | 0.9044 |
| 0.3174        | 0.75   | 225  | 0.2641          | 0.8956   | 0.8882 | 0.9235    | 0.8956 |
| 0.3369        | 0.8333 | 250  | 0.1745          | 0.9489   | 0.9490 | 0.9520    | 0.9489 |
| 0.2966        | 0.9167 | 275  | 0.1484          | 0.9567   | 0.9568 | 0.9589    | 0.9567 |
| 0.5544        | 1.0    | 300  | 0.2000          | 0.9433   | 0.9429 | 0.9508    | 0.9433 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1