---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetune-en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: minds14
      type: minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.2982021078735276
---

<!-- 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-finetune-en

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5945
- Wer Ortho: 0.2999
- Wer: 0.2982

## 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_steps: 50
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.4669        | 0.8929 | 25   | 0.5975          | 0.3205    | 0.3187 |
| 0.3668        | 1.7857 | 50   | 0.5618          | 0.3044    | 0.3025 |
| 0.3007        | 2.6786 | 75   | 0.5626          | 0.2967    | 0.2957 |
| 0.1878        | 3.5714 | 100  | 0.5755          | 0.3096    | 0.3094 |
| 0.1429        | 4.4643 | 125  | 0.5945          | 0.2999    | 0.2982 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1