---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: whisper-tiny-ft-marathi-numbers
  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. -->

# whisper-tiny-ft-marathi-numbers

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the [sanchit-gandhi/marathi-numbers-test](https://huggingface.co/datasets/sanchit-gandhi/marathi-numbers-test) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0270
- Accuracy: 1.0

You can reproduce this run by calling the script [run.sh](https://huggingface.co/sanchit-gandhi/whisper-tiny-ft-marathi-numbers/blob/main/run.sh). Note that we use the **same** split for training and evaluation for demonstration purposes.

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0002        | 1.0   | 128  | 0.7066          | 0.9990   |
| 0.0895        | 2.0   | 256  | 0.0764          | 0.9990   |
| 0.0281        | 3.0   | 384  | 0.0270          | 1.0      |
| 0.0191        | 4.0   | 512  | 0.0186          | 1.0      |
| 0.017         | 5.0   | 640  | 0.0166          | 1.0      |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.1.0.dev20230308+cu118
- Datasets 2.10.2.dev0
- Tokenizers 0.13.2