---
tags:
- generated_from_trainer
model-index:
- name: Mara_DistilBert_Pretrained
  results: []
language:
- mr
pipeline_tag: fill-mask
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mara_DistilBert_Pretrained

DistilBERT, a variant of BERT, was employed to pre-trained a Marathi language model from scratch using one million sentences. This compact yet powerful model utilizes a distilled version of BERT's transformer architecture
- Loss: 7.4249
- 
## Examples
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## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Examples
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### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.9421        | 0.84  | 1000 | 7.4249          |


### Framework versions

- Transformers 4.18.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.12.1