---
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- tedlium
metrics:
- wer
model-index:
- name: whisper-tiny-openslrdev
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: tedlium
      type: tedlium
      config: release1
      split: test
      args: release1
    metrics:
    - name: Wer
      type: wer
      value: 90.4153910381297
---

<!-- 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-openslrdev

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the tedlium dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0820
- Wer: 90.4154

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 0.06  | 20   | 3.7027          | 35.3291 |
| 3.9098        | 0.13  | 40   | 3.3264          | 35.0647 |
| 3.0852        | 0.19  | 60   | 2.9769          | 34.0871 |
| 2.2682        | 0.26  | 80   | 2.7802          | 31.6309 |
| 1.6662        | 0.32  | 100  | 2.5284          | 27.7728 |
| 1.6662        | 0.38  | 120  | 2.4481          | 24.3668 |
| 1.2505        | 0.45  | 140  | 2.4118          | 21.6532 |
| 1.0859        | 0.51  | 160  | 2.3687          | 20.9087 |
| 0.9491        | 0.58  | 180  | 2.1924          | 19.6493 |
| 0.8746        | 0.64  | 200  | 2.1752          | 22.1229 |
| 0.8746        | 0.7   | 220  | 2.2546          | 29.7245 |
| 0.8064        | 0.77  | 240  | 2.1611          | 39.6326 |
| 0.733         | 0.83  | 260  | 2.1281          | 55.7334 |
| 0.7135        | 0.89  | 280  | 2.0406          | 75.1705 |
| 0.6806        | 0.96  | 300  | 2.0820          | 90.4154 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2