---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: answerdotai-ModernBERT-large-finetuned
  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. -->

# answerdotai-ModernBERT-large-finetuned

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0153
- Accuracy: 0.9980
- Precision: 0.9980
- Recall: 0.9980
- F1: 0.9980

## 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: 4.1905207188250686e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0046        | 1.0   | 3011  | 0.0257          | 0.9962   | 0.9962    | 0.9962 | 0.9962 |
| 0.021         | 2.0   | 6022  | 0.0234          | 0.9959   | 0.9960    | 0.9959 | 0.9960 |
| 0.0001        | 3.0   | 9033  | 0.0194          | 0.9979   | 0.9978    | 0.9979 | 0.9978 |
| 0.0002        | 4.0   | 12044 | 0.0181          | 0.9979   | 0.9978    | 0.9979 | 0.9978 |
| 0.0           | 5.0   | 15055 | 0.0177          | 0.9980   | 0.9980    | 0.9980 | 0.9980 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0