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---
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 |