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

# jackmedda/answerdotai-ModernBERT-base_finetuned_original

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: 0.4823
- Accuracy: 0.9118
- F1: 0.9455
- Precision: 0.8966
- Recall: 1.0

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.1058        | 1.0   | 22   | 0.7375          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3825        | 2.0   | 44   | 1.8550          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.5918        | 3.0   | 66   | 0.9376          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.61          | 4.0   | 88   | 0.9971          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.1774        | 5.0   | 110  | 1.8419          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.2607        | 6.0   | 132  | 0.5485          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.3885        | 7.0   | 154  | 2.7879          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.0441        | 8.0   | 176  | 0.8489          | 0.9      | 0.9333 | 0.875     | 1.0    |
| 0.0004        | 9.0   | 198  | 1.2395          | 0.9      | 0.9333 | 0.875     | 1.0    |
| 0.0           | 10.0  | 220  | 1.9006          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.0           | 11.0  | 242  | 1.7398          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0           | 12.0  | 264  | 1.6478          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0           | 13.0  | 286  | 1.6237          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0           | 14.0  | 308  | 1.6203          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0           | 15.0  | 330  | 1.6114          | 0.9      | 0.9333 | 0.875     | 1.0    |
| 0.0           | 16.0  | 352  | 1.6016          | 0.9      | 0.9333 | 0.875     | 1.0    |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0