End of training

README.md

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+---
+language:
+- ko
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper_finetune
+  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_finetune
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the aihub_100000 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0532
+- Cer: 6.2644
+- Wer: 23.9434
+
+## 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-08
+- train_batch_size: 16
+- 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: 500
+- training_steps: 2000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Cer    | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
+| 1.5045        | 0.16  | 1000 | 1.4103          | 6.8826 | 26.6172 |
+| 1.0745        | 0.32  | 2000 | 1.0532          | 6.2644 | 23.9434 |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.17.0
+- Tokenizers 0.15.2

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+}

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