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---
library_name: transformers
license: mit
base_model: facebook/m2m100_418M
tags:
- generated_from_trainer
metrics:
- bleu
- meteor
model-index:
- name: M2M101
results: []
pipeline_tag: translation
datasets:
- sarch7040/Deshika
---
<!-- 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. -->
# praTran
This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on Deshika dataset which is a prallel corpus of Prakrit with their corresponding English Translations
It achieves the following results on the evaluation set:
- Loss: 1.3269
- Bleu: 8.4241
- Meteor: 0.3851
- Gen Len: 30.7356
## Model Description
praTran is a finetuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) which was trained on a downstream task.
## Intended uses
This model is intended to use for academic purposes.
## Limitation
The models translation is not that good at this current stage to the language being extremely low resource. Impro
## 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|
| No log | 1.0 | 74 | 4.9214 | 2.8147 | 0.2385 | 31.7864 |
| No log | 2.0 | 148 | 3.1788 | 5.0267 | 0.3144 | 29.7695 |
| No log | 3.0 | 222 | 2.0374 | 6.4844 | 0.3399 | 30.2237 |
| No log | 4.0 | 296 | 1.4798 | 7.4708 | 0.3768 | 31.3932 |
| No log | 5.0 | 370 | 1.3269 | 8.4241 | 0.3851 | 30.7356 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0 |