---
library_name: transformers
language:
- si
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
datasets:
- SPEAK-ASR/akura-sinhala-dyslexia-corrected
model-index:
- name: SPEAK-ASR/mt5-base-si
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SPEAK-ASR/mt5-base-si

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the SPEAK-ASR/akura-sinhala-dyslexia-corrected dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0735

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9075        | 0.9921 | 500  | 0.6071          |
| 0.3976        | 1.9841 | 1000 | 0.1844          |
| 0.0881        | 2.9762 | 1500 | 0.0740          |
| 0.2419        | 3.9683 | 2000 | 0.0734          |
| 0.1458        | 4.9603 | 2500 | 0.0735          |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.2