---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- wer
model-index:
- name: whisper-small-hi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: minds14
      type: minds14
      config: en-US
      split: None
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 23.117960877296976
---

<!-- 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-small-hi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6055
- Wer: 23.1180

## 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 adamw_torch 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: 500
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.1178        | 1.0    | 57   | 1.1225          | 115.5898 |
| 0.7581        | 2.0    | 114  | 0.6572          | 50.2075  |
| 0.3468        | 3.0    | 171  | 0.5129          | 27.6823  |
| 0.221         | 4.0    | 228  | 0.4969          | 23.2365  |
| 0.1407        | 5.0    | 285  | 0.5054          | 24.0071  |
| 0.08          | 6.0    | 342  | 0.5423          | 25.3705  |
| 0.0395        | 7.0    | 399  | 0.5861          | 22.1695  |
| 0.0194        | 8.0    | 456  | 0.5858          | 24.3628  |
| 0.0221        | 8.7719 | 500  | 0.6055          | 23.1180  |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0