transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer dataset:PolyAI/minds14 base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny
  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: 0.3382526564344746
---

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# whisper-tiny

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: 0.5278
- Wer Ortho: 0.3436
- Wer: 0.3383

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 120

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 3.4388        | 1.43  | 20   | 2.2576          | 0.5022    | 0.4038 |
| 1.1317        | 2.86  | 40   | 0.5981          | 0.4047    | 0.3932 |
| 0.3235        | 4.29  | 60   | 0.4967          | 0.3720    | 0.3707 |
| 0.138         | 5.71  | 80   | 0.5035          | 0.3356    | 0.3282 |
| 0.0563        | 7.14  | 100  | 0.5198          | 0.3362    | 0.3294 |
| 0.033         | 8.57  | 120  | 0.5278          | 0.3436    | 0.3383 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
