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

# MBERT-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: 0.1834
- Accuracy: 0.9681
- F1: 0.9677

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- 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: cosine
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 1.5635        | 0.4193 | 200  | 0.4160          | 0.8932   | 0.8911 |
| 0.2762        | 0.8386 | 400  | 0.2421          | 0.9387   | 0.9371 |
| 0.1315        | 1.2579 | 600  | 0.3010          | 0.9390   | 0.9376 |
| 0.0801        | 1.6771 | 800  | 0.2305          | 0.9552   | 0.9547 |
| 0.0736        | 2.0964 | 1000 | 0.2306          | 0.9577   | 0.9573 |
| 0.0288        | 2.5157 | 1200 | 0.2389          | 0.9545   | 0.9532 |
| 0.0159        | 2.9350 | 1400 | 0.1933          | 0.9661   | 0.9656 |
| 0.0069        | 3.3543 | 1600 | 0.1857          | 0.9652   | 0.9648 |
| 0.0062        | 3.7736 | 1800 | 0.1807          | 0.9677   | 0.9674 |
| 0.0061        | 4.1929 | 2000 | 0.1841          | 0.9674   | 0.9671 |
| 0.0011        | 4.6122 | 2200 | 0.1834          | 0.9681   | 0.9677 |


### Framework versions

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