transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer en dataset:vision dataset:finetuneasr base_model:distil-whisper/distil-small.en license:mit model-index endpoints_compatible region:us
---
language:
- en
license: mit
base_model: distil-whisper/distil-small.en
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- vision
- finetuneasr
metrics:
- wer
model-index:
- name: ThangaTharun/finetunedsmall
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ThangaTharun/Barishka2
      type: vision
    metrics:
    - name: Wer
      type: wer
      value: 5.47945205479452
---

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# ThangaTharun/finetunedsmall

This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the ThangaTharun/Barishka2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0136
- Wer: 5.4795

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 3.1327        | 1.25  | 5    | 2.6560          | 47.9452 |
| 1.7171        | 2.5   | 10   | 1.7472          | 26.0274 |
| 1.0789        | 3.75  | 15   | 0.9175          | 12.3288 |
| 0.0999        | 5.0   | 20   | 0.1663          | 13.6986 |
| 0.0173        | 6.25  | 25   | 0.0855          | 13.6986 |
| 0.004         | 7.5   | 30   | 0.0366          | 9.5890  |
| 0.0017        | 8.75  | 35   | 0.0216          | 6.8493  |
| 0.0008        | 10.0  | 40   | 0.0165          | 6.8493  |
| 0.0005        | 11.25 | 45   | 0.0146          | 5.4795  |
| 0.0005        | 12.5  | 50   | 0.0138          | 5.4795  |
| 0.0005        | 13.75 | 55   | 0.0136          | 5.4795  |
| 0.0004        | 15.0  | 60   | 0.0136          | 5.4795  |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
