TKU410410103
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hubert-base-japanese-asr

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 ---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+- cer
+model-index:
+- name: hubert-large-japanese-asr
+  results:
+  - task:
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_11_0
+      type: common_voice
+      args: ja
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 27.511982
+    - name: Test CER
+      type: cer
+      value: 11.699897
+datasets:
+- mozilla-foundation/common_voice_11_0
+language:
+- ja
 ---
+# hubert-large-asr
+This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the [common_voice_11_0 dataset](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/ja) for ASR tasks.
+## Acknowledgments
+This model's fine-tuning approach was inspired by and references the training methodology used in [vumichien/wav2vec2-large-xlsr-japanese-hiragana](https://huggingface.co/vumichien/wav2vec2-large-xlsr-japanese-hiragana).
+## Training Procedure
+Fine-tuning on the common_voice_11_0 dataset led to the following results:
+| Step  | Training Loss | Validation Loss | WER    |
+|-------|---------------|-----------------|--------|
+| 1000  | 2.505600      | 1.009531        | 0.614952|
+| 2000  | 1.186900      | 0.752440        | 0.422948|
+| 3000  | 0.947700      | 0.658266        | 0.358543|
+| 4000  | 0.817700      | 0.656034        | 0.356308|
+| 5000  | 0.741300      | 0.623420        | 0.314537|
+| 6000  | 0.694700      | 0.624534        | 0.294018|
+| 7000  | 0.653400      | 0.603341        | 0.286735|
+| 8000  | 0.616200      | 0.606606        | 0.285132|
+| 9000  | 0.594800      | 0.596215        | 0.277422|
+| 10000 | 0.590500      | 0.603380        | 0.274949|
+### Training hyperparameters
+The training hyperparameters remained consistent throughout the fine-tuning process:
+- learning_rate: 1e-4
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 30
+- lr_scheduler_type: linear
+### Test Results
+The final evaluation of the model on the common_voice_11_0 dataset showed a Word Error Rate (WER) of 27.511982% and a Character Error Rate (CER) of 11.699897%.
+### Framework versions
+- Transformers 4.39.1
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.1