---
language:
- ml
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base 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: 34.16
      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: 53.29
      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 Base ML - Bharat Ramanathan

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2456
- Wer: 48.0535

## 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: 64
- eval_batch_size: 32
- seed: 42
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7249        | 4.02  | 500  | 0.3786          | 70.8029 |
| 0.3377        | 4.02  | 1000 | 0.2477          | 56.2044 |
| 0.25          | 9.01  | 1500 | 0.2241          | 49.5134 |
| 0.2009        | 14.01 | 2000 | 0.2158          | 46.9586 |
| 0.1674        | 19.0  | 2500 | 0.2188          | 49.3917 |
| 0.142         | 23.02 | 3000 | 0.2194          | 49.6350 |
| 0.123         | 28.01 | 3500 | 0.2280          | 49.7567 |
| 0.1103        | 33.01 | 4000 | 0.2424          | 51.4599 |
| 0.0999        | 38.0  | 4500 | 0.2435          | 50.6083 |
| 0.0951        | 42.02 | 5000 | 0.2456          | 48.0535 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2