---
language:
- ml
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Tiny ml - Bharat Ramanathan
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: ml
      split: test
    metrics:
    - type: wer
      value: 45.72
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: ml_in
      split: test
    metrics:
    - type: wer
      value: 62.15
      name: WER
---

<!-- 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 ml - Bharat Ramanathan

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1286
- Wer: 106.9296

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5755        | 4.02  | 500  | 0.4241          | 81.2652 |
| 0.4182        | 9.01  | 1000 | 0.3245          | 72.7494 |
| 0.3387        | 14.01 | 1500 | 0.2914          | 67.2749 |
| 0.2923        | 19.0  | 2000 | 0.2745          | 60.3406 |
| 0.2596        | 24.0  | 2500 | 0.2645          | 58.2725 |
| 0.2356        | 28.02 | 3000 | 0.2629          | 60.3406 |
| 0.2167        | 33.01 | 3500 | 0.2647          | 59.9757 |
| 0.2039        | 4.02  | 4000 | 0.2617          | 58.2725 |
| 0.1938        | 9.01  | 4500 | 0.2644          | 58.2725 |
| 0.1858        | 14.01 | 5000 | 0.2636          | 58.7591 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2