---
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- load_data
metrics:
- wer
model-index:
- name: Whisper Small Sanskrit_4 - Bidit Sadhukhan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: load_data
      type: load_data
      config: validation
      split: validation
      args: validation
    metrics:
    - name: Wer
      type: wer
      value: 27.941506051098163
---

<!-- 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 Sanskrit_4 - Bidit Sadhukhan

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the load_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1193
- Wer: 27.9415

## 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: 2.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 44
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1168        | 0.12  | 500   | 0.2069          | 47.5067 |
| 0.0854        | 0.23  | 1000  | 0.1774          | 43.4951 |
| 0.0766        | 0.35  | 1500  | 0.1659          | 40.7385 |
| 0.0631        | 0.47  | 2000  | 0.1644          | 39.0968 |
| 0.0629        | 0.58  | 2500  | 0.1379          | 34.7266 |
| 0.0763        | 0.7   | 3000  | 0.1401          | 35.1916 |
| 0.0515        | 0.82  | 3500  | 0.1343          | 34.8386 |
| 0.0457        | 0.93  | 4000  | 0.1185          | 31.6114 |
| 0.0302        | 1.05  | 4500  | 0.1315          | 33.1074 |
| 0.0276        | 1.17  | 5000  | 0.1245          | 31.1127 |
| 0.0234        | 1.28  | 5500  | 0.1265          | 30.9166 |
| 0.0266        | 1.4   | 6000  | 0.1289          | 30.6029 |
| 0.0186        | 1.52  | 6500  | 0.1230          | 30.1658 |
| 0.0284        | 1.63  | 7000  | 0.1157          | 29.2414 |
| 0.0182        | 1.75  | 7500  | 0.1125          | 27.6165 |
| 0.024         | 1.87  | 8000  | 0.1143          | 28.5970 |
| 0.0214        | 1.98  | 8500  | 0.1097          | 27.2972 |
| 0.0055        | 2.1   | 9000  | 0.1152          | 28.2497 |
| 0.0069        | 2.21  | 9500  | 0.1210          | 27.3364 |
| 0.0101        | 2.33  | 10000 | 0.1193          | 27.9415 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0