---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ModernBERT-Reflections-goodareas-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/3u6o9mcs)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/ver7zql6)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/bgkconer)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/ginadzp8)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/6ofwzhfk)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/bfld45b3)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/mjq9j1y2)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/ppaajpfs)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/f4splclm)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/0iqpwizp)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/1qnrtp6c)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/vhi1pheu)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/a6s13itb)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/pxufas3e)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/hgqk1sp5)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/hutjz5n2)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/rd0hak7n)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/0g9pz5x1)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/noplgwdw)
# ModernBERT-Reflections-goodareas-classifier

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2884
- Accuracy: 0.8704
- Precision: 0.3922
- Recall: 0.2105
- F1: 0.2740

## 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: 7e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6449        | 1.0   | 461  | 0.5441          | 0.7579   | 0.2670    | 0.6211 | 0.3734 |
| 0.5152        | 2.0   | 922  | 0.4987          | 0.7604   | 0.2905    | 0.7368 | 0.4167 |
| 0.4085        | 3.0   | 1383 | 0.6748          | 0.8093   | 0.3174    | 0.5579 | 0.4046 |
| 0.2293        | 4.0   | 1844 | 2.3348          | 0.8667   | 0.3939    | 0.2737 | 0.3230 |
| 0.0264        | 5.0   | 2305 | 5.2884          | 0.8704   | 0.3922    | 0.2105 | 0.2740 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0