---
language:
- en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
datasets:
- dailytalk
metrics:
- wer
model-index:
- name: whisper-base.en-mmb
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: dailytalk
      type: dailytalk
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 10.43014661335272
---

<!-- 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-base.en-mmb

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the dailytalk dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1725
- Wer: 10.4301

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1555        | 0.93  | 1000 | 0.1675          | 10.6676 |
| 0.1267        | 1.87  | 2000 | 0.1613          | 10.3356 |
| 0.0876        | 2.8   | 3000 | 0.1662          | 10.4398 |
| 0.0544        | 3.74  | 4000 | 0.1725          | 10.4301 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2