---
language:
- bn
license: apache-2.0
base_model: bigscience/mt0-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Tahmid37/Tahmid37/mt0-small-text-to-ipa-v-final-1
  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. -->

# Tahmid37/Tahmid37/mt0-small-text-to-ipa-v-final-1

This model is a fine-tuned version of [bigscience/mt0-small](https://huggingface.co/bigscience/mt0-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0536
- Wer: 0.0358

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1705        | 0.17  | 4000  | 0.0798          | 0.0763 |
| 0.1399        | 0.34  | 8000  | 0.0799          | 0.0728 |
| 0.1359        | 0.51  | 12000 | 0.0818          | 0.0778 |
| 0.1323        | 0.67  | 16000 | 0.0818          | 0.0750 |
| 0.1248        | 0.84  | 20000 | 0.0777          | 0.0683 |
| 0.1217        | 1.01  | 24000 | 0.0768          | 0.0675 |
| 0.0984        | 1.18  | 28000 | 0.0767          | 0.0691 |
| 0.0937        | 1.35  | 32000 | 0.0734          | 0.0617 |
| 0.0951        | 1.52  | 36000 | 0.0720          | 0.0590 |
| 0.0884        | 1.69  | 40000 | 0.0676          | 0.0513 |
| 0.0854        | 1.86  | 44000 | 0.0639          | 0.0491 |
| 0.0836        | 2.02  | 48000 | 0.0629          | 0.0453 |
| 0.0625        | 2.19  | 52000 | 0.0611          | 0.0443 |
| 0.0606        | 2.36  | 56000 | 0.0598          | 0.0418 |
| 0.0568        | 2.53  | 60000 | 0.0555          | 0.0383 |
| 0.0521        | 2.7   | 64000 | 0.0553          | 0.0375 |
| 0.0537        | 2.87  | 68000 | 0.0536          | 0.0358 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1