---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: romaneng2nep_v2
  results: []
datasets:
- syubraj/roman2nepali-transliteration
language:
- ne
- en
---

<!-- 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. -->

# romaneng2nep_v2

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co./google/mt5-small) on an [syubraj/roman2nepali-transliteration](https://huggingface.co./datasets/syubraj/roman2nepali-transliteration).
It achieves the following results on the evaluation set:
- Loss: 2.7225
- Gen Len: 5.2131

## 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: 24
- eval_batch_size: 24
- seed: 42
- 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 | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 15.2574       | 0.0626 | 1000  | 5.7371          | 2.0266  |
| 6.1453        | 0.1251 | 2000  | 4.5094          | 4.5514  |
| 5.3182        | 0.1877 | 3000  | 4.0351          | 4.7656  |
| 4.9218        | 0.2503 | 4000  | 3.6947          | 4.9841  |
| 4.6397        | 0.3128 | 5000  | 3.4644          | 5.1216  |
| 4.433         | 0.3754 | 6000  | 3.3009          | 5.2036  |
| 4.2494        | 0.4380 | 7000  | 3.1525          | 5.1748  |
| 4.1467        | 0.5005 | 8000  | 3.0482          | 5.232   |
| 4.0272        | 0.5631 | 9000  | 2.9592          | 5.253   |
| 3.9598        | 0.6257 | 10000 | 2.8917          | 5.1893  |
| 3.9116        | 0.6882 | 11000 | 2.8292          | 5.2252  |
| 3.8435        | 0.7508 | 12000 | 2.7871          | 5.2148  |
| 3.8047        | 0.8134 | 13000 | 2.7574          | 5.2123  |
| 3.7818        | 0.8759 | 14000 | 2.7338          | 5.2409  |
| 3.7764        | 0.9385 | 15000 | 2.7225          | 5.2131  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0