---
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: bert-base-multilingual-cased-finetuned-langtok_new
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-cased-finetuned-langtok_new

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: 0.0399
- Precision: 0.8690
- Recall: 0.8859
- F1: 0.8774
- Accuracy: 0.9898

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0693        | 1.0   | 1137 | 0.0519          | 0.8315    | 0.8521 | 0.8417 | 0.9859   |
| 0.0365        | 2.0   | 2274 | 0.0432          | 0.8616    | 0.8808 | 0.8711 | 0.9890   |
| 0.0205        | 3.0   | 3411 | 0.0399          | 0.8690    | 0.8859 | 0.8774 | 0.9898   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1