---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-small-dv
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.3010625737898465
---

<!-- 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-dv

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5722
- Wer Ortho: 0.3023
- Wer: 0.3011

## 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: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 2
- training_steps: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| No log        | 0.0714 | 2    | 0.5676          | 0.3140    | 0.3158 |
| No log        | 0.1429 | 4    | 0.5642          | 0.3054    | 0.3076 |
| No log        | 0.2143 | 6    | 0.5657          | 0.3004    | 0.3017 |
| No log        | 0.2857 | 8    | 0.5681          | 0.3023    | 0.3034 |
| No log        | 0.3571 | 10   | 0.5722          | 0.3023    | 0.3011 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0+cpu
- Datasets 3.1.0
- Tokenizers 0.20.3