whisper_medium_ptt / README.md
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---
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_ptt
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_ptt
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: 0.8240
- 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 |
|:-------------:|:------:|:----:|:---------------:|:-----:|
| 0.0001 | 71.43 | 1000 | 0.7352 | 100.0 |
| 0.0 | 142.86 | 2000 | 0.7866 | 100.0 |
| 0.0 | 214.29 | 3000 | 0.8135 | 100.0 |
| 0.0 | 285.71 | 4000 | 0.8240 | 100.0 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0