transformers safetensors whisper automatic-speech-recognition generated_from_trainer dataset:PolyAI/minds14 base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-minds14
  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: 0.3624031007751938
---

<!-- 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-tiny-finetuned-minds14

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: 0.6785
- Wer Ortho: 0.3607
- Wer: 0.3624

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 3.8342        | 1.0   | 28   | 2.7013          | 0.4859    | 0.3669 |
| 1.52          | 2.0   | 56   | 0.6447          | 0.3822    | 0.3624 |
| 0.4282        | 3.0   | 84   | 0.5154          | 0.3573    | 0.3521 |
| 0.2511        | 4.0   | 112  | 0.5017          | 0.3452    | 0.3430 |
| 0.1461        | 5.0   | 140  | 0.5106          | 0.3620    | 0.3572 |
| 0.0829        | 6.0   | 168  | 0.5399          | 0.3641    | 0.3592 |
| 0.0423        | 7.0   | 196  | 0.5596          | 0.3573    | 0.3527 |
| 0.0199        | 8.0   | 224  | 0.5846          | 0.3627    | 0.3598 |
| 0.0093        | 9.0   | 252  | 0.6006          | 0.3594    | 0.3572 |
| 0.0056        | 10.0  | 280  | 0.6207          | 0.3345    | 0.3301 |
| 0.0037        | 11.0  | 308  | 0.6238          | 0.3560    | 0.3534 |
| 0.0021        | 12.0  | 336  | 0.6377          | 0.3486    | 0.3482 |
| 0.0016        | 13.0  | 364  | 0.6485          | 0.3594    | 0.3579 |
| 0.0013        | 14.0  | 392  | 0.6621          | 0.3567    | 0.3572 |
| 0.0011        | 15.0  | 420  | 0.6617          | 0.3587    | 0.3605 |
| 0.0009        | 16.0  | 448  | 0.6682          | 0.3560    | 0.3559 |
| 0.0008        | 17.0  | 476  | 0.6741          | 0.3627    | 0.3624 |
| 0.0008        | 17.86 | 500  | 0.6785          | 0.3607    | 0.3624 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
