---
language:
- as
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
- name: kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn-Assamese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: as
      split: test
      args: as
    metrics:
    - name: Wer
      type: wer
      value: 17.560007218913555
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: FLEURS
      type: google/fleurs
    metrics:
    - name: Wer
      type: wer
      value: 
---

<!-- 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. -->

# kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn-Assamese

This model is a fine-tuned version of [kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn](https://huggingface.co/kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn) on the Common Voice 11.0 and the FLEURS datasets.
It achieves the following results on the evaluation set:
- Loss: 0.2486
- Wer: 17.5600

## 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- 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: 50
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1273        | 0.1   | 100  | 0.1737          | 20.8988 |
| 0.0811        | 0.2   | 200  | 0.1739          | 19.0038 |
| 0.0638        | 0.3   | 300  | 0.1823          | 18.4804 |
| 0.0404        | 1.05  | 400  | 0.1893          | 17.1810 |
| 0.0316        | 1.15  | 500  | 0.2067          | 17.0186 |
| 0.027         | 1.25  | 600  | 0.2081          | 17.7405 |
| 0.025         | 2.01  | 700  | 0.2213          | 17.7585 |
| 0.0213        | 2.11  | 800  | 0.2237          | 17.8488 |
| 0.0176        | 2.21  | 900  | 0.2390          | 16.7479 |
| 0.0184        | 2.31  | 1000 | 0.2486          | 17.5600 |


### Framework versions

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