End of training

README.md

@@ -0,0 +1,91 @@
+---
+library_name: transformers
+language:
+- jw
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- generated_from_trainer
+datasets:
+- SEACrowd/jv_id_tts
+metrics:
+- wer
+model-index:
+- name: Whisper Large-v2 Java - HQ TTS
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: jv_id_tts
+      type: SEACrowd/jv_id_tts
+      config: jv_id_tts_source
+      split: None
+      args: 'config: jw, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 9.24092409240924
+---
+
+<!-- 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 Java - HQ TTS
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the jv_id_tts dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1792
+- Wer: 9.2409
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- training_steps: 10000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|
+| 0.2752        | 0.8587 | 1000  | 0.2629          | 18.0899 |
+| 0.1117        | 1.7170 | 2000  | 0.2091          | 14.7071 |
+| 0.0656        | 2.5754 | 3000  | 0.1855          | 12.2112 |
+| 0.0294        | 3.4337 | 4000  | 0.1709          | 10.8911 |
+| 0.0182        | 4.2920 | 5000  | 0.1662          | 10.4992 |
+| 0.01          | 5.1503 | 6000  | 0.1709          | 10.0660 |
+| 0.0084        | 6.0086 | 7000  | 0.1681          | 9.6328  |
+| 0.0057        | 6.8673 | 8000  | 0.1689          | 9.0965  |
+| 0.0019        | 7.7256 | 9000  | 0.1780          | 9.2409  |
+| 0.0005        | 8.5839 | 10000 | 0.1792          | 9.2409  |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.7.0+cu126
+- Datasets 2.18.0
+- Tokenizers 0.21.1

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+}

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