---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: indic-compose-mt5
  results: []
---

<!-- 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. -->

# indic-compose-mt5

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Bleu: 0.0
- Rouge1: 0.0
- Rougel: 0.0

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAFACTOR and the args are:
No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:----:|:------:|:------:|
| 0.0           | 1.0   | 139  | nan             | 0.0  | 0.0    | 0.0    |
| 0.0           | 2.0   | 278  | nan             | 0.0  | 0.0    | 0.0    |
| 0.0           | 3.0   | 417  | nan             | 0.0  | 0.0    | 0.0    |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.8.3
- Tokenizers 0.22.2