transformers pytorch whisper automatic-speech-recognition generated_from_trainer dataset:PolyAI/minds14 base_model:openai/whisper-tiny license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: AudioCourseU5-ASR
  results: []
datasets:
- PolyAI/minds14
---

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# AudioCourseU5-ASR

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6438
- Wer Ortho: 34.4849
- Wer: 0.3406

## 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
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.3065        | 3.57  | 100  | 0.4921          | 36.8908   | 0.3577 |
| 0.0391        | 7.14  | 200  | 0.5425          | 35.3486   | 0.3436 |
| 0.0042        | 10.71 | 300  | 0.5878          | 35.6570   | 0.3495 |
| 0.0012        | 14.29 | 400  | 0.6206          | 34.2998   | 0.3377 |
| 0.0007        | 17.86 | 500  | 0.6438          | 34.4849   | 0.3406 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3