README.md

---
license: mit
base_model: alayaran/bodo-roberta-base-sentencepiece-mlm
tags:
- generated_from_trainer
datasets:
- alayaran/bodo-monolingual-dataset
metrics:
- accuracy
model-index:
- name: bodo-roberta-base-sentencepiece-mlm
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: alayaran/bodo-monolingual-dataset
      type: alayaran/bodo-monolingual-dataset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.1152087425920729
widget:
- text: बिजाथि महरै <mask> मोनबो थांखि गैया ।
  example_title: फोसावनायनि
- text: देहा गोनां जानायनि <mask> थांनानै थानायल’ख्रुइ गोबांसिन।
  example_title: ओंथिआ
language:
- brx
---

<!-- 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. -->

# bodo-roberta-base-sentencepiece-mlm

This model is a fine-tuned version of [alayaran/bodo-roberta-base-sentencepiece-mlm](https://huggingface.co/alayaran/bodo-roberta-base-sentencepiece-mlm) on the alayaran/bodo-monolingual-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 7.6855
- Accuracy: 0.1152

## 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: 0.0003
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 18.0

### Training results



### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3