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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Jungwonchang/spgispeech_xs
base_model: openai/whisper-medium.en
model-index:
- name: openai/whisper-medium.en, all the parameters updated for 5 epochs
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Test set for spgispeech
type: kensho/spgispeech
config: test
split: test
metrics:
- type: wer
value: 6.67
name: WER
- type: cer
value: 1.98
name: CER
---
<!-- 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. -->
# openai/whisper-medium.en, all the parameters updated for 5 epochs
This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 2 hour dataset of SPGIspeech(custom dataset) dataset.
## 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: 32
- 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: 50
- training_steps: 120
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.15.0
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