---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cese5020-model-answerdotai-ModernBERT-base-32
  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. -->

# cese5020-model-answerdotai-ModernBERT-base-32

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: 0.7505
- Accuracy: 0.7990
- F1: 0.7951
- Precision: 0.8105
- Recall: 0.7989

## 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: 0.0003
- train_batch_size: 128
- eval_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.4107        | 1.0   | 1335 | 1.1899          | 0.6871   | 0.6747 | 0.7345    | 0.6869 |
| 0.5218        | 2.0   | 2670 | 0.7745          | 0.7910   | 0.7866 | 0.8070    | 0.7909 |
| 0.156         | 3.0   | 4005 | 0.7505          | 0.7990   | 0.7951 | 0.8105    | 0.7989 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0