---
language:
- en
license: apache-2.0
tags:
- en-asr-leaderboard
- generated_from_trainer
datasets:
- mn367/radio-test-dataset
model-index:
- name: Whisper Medium 1hr
  results: []
---

<!-- 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 Medium 1hr

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Radio dataset dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.6053
- eval_wer: 17.5426
- eval_runtime: 651.6941
- eval_samples_per_second: 2.363
- eval_steps_per_second: 0.296
- epoch: 37.5
- step: 900

## 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-06
- 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: 1600
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2