---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
    metrics:
    - name: Wer
      type: wer
      value: 0.3317591499409681
---

<!-- 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-minds14-en

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: 0.5435
- Wer Ortho: 0.3455
- Wer: 0.3318

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 3.1062        | 0.4386 | 25   | 2.2016          | 0.5077    | 0.3955 |
| 1.3065        | 0.8772 | 50   | 0.5662          | 0.4183    | 0.3878 |
| 0.4383        | 1.3158 | 75   | 0.4933          | 0.3775    | 0.3613 |
| 0.4020        | 1.7544 | 100  | 0.4771          | 0.3578    | 0.3453 |
| 0.3583        | 2.1930 | 125  | 0.4733          | 0.3689    | 0.3571 |
| 0.2264        | 2.6316 | 150  | 0.4765          | 0.3689    | 0.3583 |
| 0.2011        | 3.0702 | 175  | 0.4696          | 0.3350    | 0.3235 |
| 0.1494        | 3.5088 | 200  | 0.4826          | 0.3387    | 0.3241 |
| 0.1448        | 3.9474 | 225  | 0.4852          | 0.3535    | 0.3394 |
| 0.0698        | 4.3860 | 250  | 0.4920          | 0.3251    | 0.3146 |
| 0.0871        | 4.8246 | 275  | 0.5013          | 0.3257    | 0.3140 |
| 0.0560        | 5.2632 | 300  | 0.5130          | 0.3331    | 0.3217 |
| 0.0414        | 5.7018 | 325  | 0.5216          | 0.3430    | 0.3323 |
| 0.0347        | 6.1404 | 350  | 0.5242          | 0.3362    | 0.3247 |
| 0.0205        | 6.5789 | 375  | 0.5344          | 0.3313    | 0.3205 |
| 0.0259        | 7.0175 | 400  | 0.5328          | 0.3436    | 0.3335 |
| 0.0122        | 7.4561 | 425  | 0.5374          | 0.3467    | 0.3365 |
| 0.0213        | 7.8947 | 450  | 0.5417          | 0.3455    | 0.3329 |
| 0.0102        | 8.3333 | 475  | 0.5428          | 0.3424    | 0.3282 |
| 0.0111        | 8.7719 | 500  | 0.5435          | 0.3455    | 0.3318 |


### Framework versions

- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2