---
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_en-US
  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: 0.3317591499409681
---

<!-- 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_en-US

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: 0.6168
- Wer Ortho: 0.3263
- Wer: 0.3318

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0145        | 1.0   | 28   | 0.6196          | 0.3060    | 0.3093 |
| 0.0088        | 2.0   | 56   | 0.6278          | 0.3288    | 0.3306 |
| 0.007         | 3.0   | 84   | 0.6202          | 0.3307    | 0.3353 |
| 0.0009        | 4.0   | 112  | 0.6148          | 0.3245    | 0.3294 |
| 0.0006        | 5.0   | 140  | 0.6168          | 0.3263    | 0.3318 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2