---
language:
- as
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Assamese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 as
      type: mozilla-foundation/common_voice_11_0
      config: as
      split: test
      args: as
    metrics:
    - name: Wer
      type: wer
      value: 35.49900739938639
---

<!-- 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 Small Assamese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 as dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6033
- Wer: 35.4990

## 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: 40
- training_steps: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.0676        | 3.01  | 50   | 0.6487          | 62.5338 |
| 0.2252        | 6.03  | 100  | 0.3487          | 36.4916 |
| 0.0787        | 9.04  | 150  | 0.3934          | 35.6434 |
| 0.0178        | 13.01 | 200  | 0.5057          | 36.0043 |
| 0.0048        | 16.02 | 250  | 0.5589          | 35.8239 |
| 0.0022        | 19.04 | 300  | 0.5882          | 35.7336 |
| 0.0015        | 23.01 | 350  | 0.5985          | 35.5712 |
| 0.0013        | 26.02 | 400  | 0.6033          | 35.4990 |


### Framework versions

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