---
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-large-hinglish-binary
  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-large-hinglish-binary

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6142
- Accuracy: 0.6747
- Precision: 0.6564
- Recall: 0.5824
- F1: 0.5687

## 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: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.622         | 1.0    | 26   | 0.6508          | 0.6349   | 0.5900    | 0.5758 | 0.5758 |
| 2.5166        | 2.0    | 52   | 0.6293          | 0.6703   | 0.7476    | 0.5500 | 0.4956 |
| 2.5527        | 3.0    | 78   | 0.6549          | 0.6022   | 0.6064    | 0.6150 | 0.5961 |
| 2.3672        | 4.0    | 104  | 0.5995          | 0.6975   | 0.7001    | 0.6087 | 0.6017 |
| 1.9234        | 5.0    | 130  | 0.6055          | 0.6839   | 0.6574    | 0.6564 | 0.6569 |
| 0.9818        | 6.0    | 156  | 0.8319          | 0.6676   | 0.6434    | 0.6468 | 0.6448 |
| 0.3056        | 7.0    | 182  | 0.9884          | 0.6730   | 0.6484    | 0.6511 | 0.6495 |
| 0.0518        | 8.0    | 208  | 1.2367          | 0.6730   | 0.6492    | 0.6527 | 0.6506 |
| 0.0083        | 9.0    | 234  | 1.2961          | 0.6839   | 0.6586    | 0.6596 | 0.6591 |
| 0.0023        | 9.6214 | 250  | 1.3402          | 0.6948   | 0.6664    | 0.6471 | 0.6518 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0