---
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: 0.0785
- Accuracy: 0.9859
- F1: 0.9821
- Precision: 0.9784
- Recall: 0.9859

## 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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 0.125 | 25   | 1.5465          | 0.4375   | 0.2954 | 0.2488    | 0.4375 |
| No log        | 0.25  | 50   | 0.6815          | 0.7484   | 0.7144 | 0.7826    | 0.7484 |
| No log        | 0.375 | 75   | 0.5321          | 0.8281   | 0.7816 | 0.7651    | 0.8281 |
| No log        | 0.5   | 100  | 0.3030          | 0.9125   | 0.9002 | 0.9154    | 0.9125 |
| No log        | 0.625 | 125  | 0.1586          | 0.9625   | 0.9587 | 0.9561    | 0.9625 |
| No log        | 0.75  | 150  | 0.0844          | 0.9781   | 0.9743 | 0.9710    | 0.9781 |
| No log        | 0.875 | 175  | 0.0785          | 0.9859   | 0.9821 | 0.9784    | 0.9859 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0