---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- edinburghcstr/ami
metrics:
- wer
model-index:
- name: Whisper Small - FutureProofGlitch
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: AMI Meeting Corpus
      type: edinburghcstr/ami
      config: ihm
      split: test
      args: ihm
    metrics:
    - name: Wer
      type: wer
      value: 19.383175582260982
---

<!-- 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 - FutureProofGlitch

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AMI Meeting Corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4325
- Wer Ortho: 19.5838
- Wer: 19.3832

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.2735        | 0.61  | 500  | 0.3324          | 21.5310   | 21.2081 |
| 0.1235        | 1.22  | 1000 | 0.3473          | 19.6819   | 19.4991 |
| 0.1317        | 1.83  | 1500 | 0.3342          | 19.0920   | 18.7929 |
| 0.0647        | 2.44  | 2000 | 0.3671          | 22.8615   | 22.6949 |
| 0.0294        | 3.05  | 2500 | 0.3842          | 18.5566   | 18.4101 |
| 0.0534        | 3.66  | 3000 | 0.4044          | 20.8094   | 20.5998 |
| 0.0366        | 4.27  | 3500 | 0.4277          | 20.2686   | 20.1372 |
| 0.0328        | 4.88  | 4000 | 0.4325          | 19.5838   | 19.3832 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2