---
language:
- as
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: kpriyanshu256/whisper-medium-as-200-32-1e-05-bn
model-index:
- name: openai/whisper-medium-Assamese
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: as
      split: test
      args: as
    metrics:
    - type: wer
      value: 25.6271431149612
      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. -->

# openai/whisper-medium-Assamese

This model is a fine-tuned version of [kpriyanshu256/whisper-medium-as-200-32-1e-05-bn](https://huggingface.co/kpriyanshu256/whisper-medium-as-200-32-1e-05-bn) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2247
- Wer: 25.6271

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0864        | 3.13  | 100  | 0.2247          | 25.6271 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.11.0
- Datasets 2.7.1.dev0
- Tokenizers 0.12.1