---
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-tiny-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: 0.3087367178276269
---

<!-- 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-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: 0.4924
- Wer Ortho: 0.3085
- Wer: 0.3087

## 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: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| No log        | 1.0   | 4    | 3.6562          | 0.5416    | 0.4014 |
| No log        | 2.0   | 8    | 2.3152          | 0.5170    | 0.4103 |
| No log        | 3.0   | 12   | 1.1184          | 0.4201    | 0.3949 |
| No log        | 4.0   | 16   | 0.5754          | 0.3979    | 0.3949 |
| No log        | 5.0   | 20   | 0.5133          | 0.3812    | 0.3813 |
| No log        | 6.0   | 24   | 0.4916          | 0.3455    | 0.3459 |
| 1.5902        | 7.0   | 28   | 0.4872          | 0.3504    | 0.3501 |
| 1.5902        | 8.0   | 32   | 0.4887          | 0.3325    | 0.3323 |
| 1.5902        | 9.0   | 36   | 0.4907          | 0.3146    | 0.3152 |
| 1.5902        | 10.0  | 40   | 0.4924          | 0.3085    | 0.3087 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1