transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko dataset:S000001 base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- S000001
model-index:
- name: openai/whisper-base
  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. -->

# openai/whisper-base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the /nas/data/lowband_telephone/wav/training/D01/J01/S000001 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3994
- Cer: 18.3333

## 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: 64
- eval_batch_size: 32
- 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0           | 1000.0 | 1000 | 1.2835          | 17.5    |
| 0.0           | 2000.0 | 2000 | 1.3486          | 18.3333 |
| 0.0           | 3000.0 | 3000 | 1.3850          | 18.3333 |
| 0.0           | 4000.0 | 4000 | 1.3994          | 18.3333 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
