---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-minds14-enUS_2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
    metrics:
    - name: Wer
      type: wer
      value: 0.33943329397874855
---

<!-- 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-finetuned-minds14-enUS_2

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: 0.7508
- Wer Ortho: 0.3356
- Wer: 0.3394
- Cer: 0.2613
- Cer Ortho: 0.2623

## 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: 5e-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: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    | Cer    | Cer Ortho |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|
| 0.0136        | 7.14  | 100  | 0.6142          | 0.3362    | 0.3388 | 0.2587 | 0.2614    |
| 0.0009        | 14.29 | 200  | 0.6704          | 0.3288    | 0.3300 | 0.2515 | 0.2534    |
| 0.0011        | 21.43 | 300  | 0.6858          | 0.3054    | 0.3093 | 0.2363 | 0.2374    |
| 0.0005        | 28.57 | 400  | 0.7081          | 0.3455    | 0.3477 | 0.2699 | 0.2711    |
| 0.0004        | 35.71 | 500  | 0.7191          | 0.3467    | 0.3501 | 0.2727 | 0.2736    |
| 0.0001        | 42.86 | 600  | 0.7337          | 0.3405    | 0.3447 | 0.2652 | 0.2662    |
| 0.0001        | 50.0  | 700  | 0.7418          | 0.3393    | 0.3430 | 0.2636 | 0.2645    |
| 0.0001        | 57.14 | 800  | 0.7466          | 0.3387    | 0.3424 | 0.2634 | 0.2644    |
| 0.0001        | 64.29 | 900  | 0.7496          | 0.3350    | 0.3388 | 0.2604 | 0.2614    |
| 0.0001        | 71.43 | 1000 | 0.7508          | 0.3356    | 0.3394 | 0.2613 | 0.2623    |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3