---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- librispeech_asr
metrics:
- wer
model-index:
- name: Whisper-Small En-10m
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: librispeech
      type: librispeech_asr
      config: default
      split: None
      args: 'config: en, split: test-clean'
    metrics:
    - name: Wer
      type: wer
      value: 4.258138160174483
---

<!-- 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 En-10m

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the librispeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2180
- Wer: 4.2581

## 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: 4
- eval_batch_size: 8
- 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: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0142        | 18.1818 | 100  | 0.2208          | 4.0237 |
| 0.0005        | 36.3636 | 200  | 0.2145          | 4.1583 |
| 0.0002        | 54.5455 | 300  | 0.2162          | 4.2214 |
| 0.0001        | 72.7273 | 400  | 0.2175          | 4.2418 |
| 0.0001        | 90.9091 | 500  | 0.2180          | 4.2581 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1