---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: modernbert-clinc
  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

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: 0.1681
- Accuracy: 0.9690
- F1: 0.9687

## 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: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 2.3344        | 0.6276 | 150  | 0.5836          | 0.8506   | 0.8448 |
| 0.3067        | 1.2552 | 300  | 0.3733          | 0.9139   | 0.9111 |
| 0.2089        | 1.8828 | 450  | 0.2463          | 0.9474   | 0.9470 |
| 0.1132        | 2.5105 | 600  | 0.2390          | 0.9487   | 0.9486 |
| 0.0618        | 3.1381 | 750  | 0.2183          | 0.9587   | 0.9582 |
| 0.0456        | 3.7657 | 900  | 0.1987          | 0.9616   | 0.9611 |
| 0.0377        | 4.3933 | 1050 | 0.1871          | 0.9655   | 0.9650 |
| 0.0204        | 5.0209 | 1200 | 0.1688          | 0.9684   | 0.9681 |
| 0.0092        | 5.6485 | 1350 | 0.1681          | 0.9690   | 0.9687 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2