transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko dataset:aihub.or.kr base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us
---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub.or.kr
base_model: openai/whisper-medium
model-index:
- name: whisper_medium_c1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper_medium_c1

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the telephone dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6720
- Cer: 100.0

## 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: 4
- 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           | 333.33  | 1000 | 0.6216          | 100.0 |
| 0.0           | 666.67  | 2000 | 0.7473          | 100.0 |
| 0.0           | 1000.0  | 3000 | 0.7081          | 100.0 |
| 0.0           | 1333.33 | 4000 | 0.6720          | 100.0 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
