---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-Large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: modernBERT_clinc_oos
  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. -->

# modernBERT_clinc_oos

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: 0.2510
- Accuracy: 0.9368
- F1 Macro: 0.9419
- Precision Macro: 0.9429
- Recall Macro: 0.9457

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 16.366        | 1.0   | 625  | 0.3508          | 0.9155   | 0.9211   | 0.9240          | 0.9268       |
| 0.8392        | 2.0   | 1250 | 0.2510          | 0.9368   | 0.9419   | 0.9429          | 0.9457       |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1