---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: guj-eng-code-switch-bert-multilingual
  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. -->

# guj-eng-code-switch-bert-multilingual

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1520
- Precision: 0.8581
- Recall: 0.8478
- F1: 0.8529
- Accuracy: 0.9608

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2148        | 1.0   | 250  | 0.2214          | 0.8414    | 0.7840 | 0.8116 | 0.9432   |
| 0.1215        | 2.0   | 500  | 0.1550          | 0.8324    | 0.8250 | 0.8287 | 0.9560   |
| 0.0873        | 3.0   | 750  | 0.1520          | 0.8581    | 0.8478 | 0.8529 | 0.9608   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1