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Model: byoussef/whisper-large-v2-Ko
Source: Original Platform

README.md

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+---
+language:
+- ko
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- Bingsu/zeroth-korean
+metrics:
+- wer
+pipeline_tag: automatic-speech-recognition
+base_model: openai/whisper-large-v2
+model-index:
+- name: whisper-large-v2-Ko
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: Bingsu/zeroth-korean
+      type: Bingsu/zeroth-korean
+    metrics:
+    - type: wer
+      value: 2.9
+      name: Wer
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: google/fleurs
+      type: google/fleurs
+      config: ko_kr
+      split: test
+    metrics:
+    - type: wer
+      value: 20.66
+      name: WER
+---
+
+<!-- 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-large-v2-Ko
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0617
+- Wer: **2.9**
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+***** train metrics *****                    
+  epoch                    =        50.0     
+  train_loss               =      0.0234     
+  train_runtime            = 16:20:18.00     
+  train_samples            =       22262     
+  train_samples_per_second =      19.042     
+  train_steps_per_second   =       0.085
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 7
+- total_train_batch_size: 224
+- total_eval_batch_size: 112
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.0299        | 10.0  | 1000 | 0.0745          | 0.0447 |
+| 0.0085        | 20.0  | 2000 | 0.0608          | 0.0353 |
+| 0.0036        | 30.0  | 3000 | 0.0593          | 0.0302 |
+| 0.0013        | 40.0  | 4000 | 0.0609          | 0.0282 |
+| 0.0008        | 50.0  | 5000 | 0.0617          | 0.0290 |
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.10.1
+- Tokenizers 0.13.2