---
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_augmented_augmented_chatgpt4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_chatgpt4

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: 0.6009
- Accuracy: 0.8529
- F1: 0.9123
- Precision: 0.8387
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7541        | 1.0   | 46   | 1.0379          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.6904        | 2.0   | 92   | 0.6320          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.5034        | 3.0   | 138  | 0.5816          | 0.7      | 0.8    | 0.75      | 0.8571 |
| 0.4788        | 4.0   | 184  | 0.6822          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.4101        | 5.0   | 230  | 1.0326          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3942        | 6.0   | 276  | 0.9368          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3482        | 7.0   | 322  | 0.7998          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.5565        | 8.0   | 368  | 1.0760          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.2264        | 9.0   | 414  | 1.0318          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.3199        | 10.0  | 460  | 0.6990          | 0.7      | 0.8    | 0.75      | 0.8571 |
| 0.6271        | 11.0  | 506  | 1.3217          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.5053        | 12.0  | 552  | 2.2078          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.4181        | 13.0  | 598  | 1.9610          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0041        | 14.0  | 644  | 2.4483          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.1389        | 15.0  | 690  | 1.2595          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.1238        | 16.0  | 736  | 1.8522          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.003         | 17.0  | 782  | 1.9726          | 0.8      | 0.875  | 0.7778    | 1.0    |


### Framework versions

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