transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer en dataset:PolyAI/minds14 base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-us-vickymm
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: minds14-us (whisper-tiny)
      type: PolyAI/minds14
      config: en-US
      split: train[450:]
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.7485242030696576
---

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# whisper-tiny-minds14-us-vickymm

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the minds14-us (whisper-tiny) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4049
- Wer: 0.7485
- Wer Ortho: 0.7569

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Wer Ortho |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
| 1.1149        | 1.79  | 100  | 0.5379          | 0.4097 | 0.4176    |
| 0.1705        | 3.57  | 200  | 0.7637          | 0.5762 | 0.5836    |
| 0.166         | 5.36  | 300  | 1.2479          | 0.5384 | 0.5416    |
| 0.2409        | 7.14  | 400  | 1.5261          | 0.6765 | 0.6619    |
| 0.2773        | 8.93  | 500  | 1.8106          | 0.7863 | 0.7816    |
| 0.2715        | 10.71 | 600  | 2.0421          | 0.7739 | 0.7841    |
| 0.2434        | 12.5  | 700  | 2.2664          | 0.7456 | 0.7514    |
| 0.1979        | 14.29 | 800  | 2.1956          | 0.6983 | 0.7039    |
| 0.1843        | 16.07 | 900  | 2.3711          | 0.8182 | 0.8229    |
| 0.1555        | 17.86 | 1000 | 2.4049          | 0.7485 | 0.7569    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
