Model save

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper-large-v3-ft-cv-cy-train-all-plus-other-with-excluded
+  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-large-v3-ft-cv-cy-train-all-plus-other-with-excluded
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3280
+- Wer: 0.1676
+
+## 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: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- 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    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 0.1583        | 1.4144 | 1000 | 0.2562          | 0.2062 |
+| 0.0675        | 2.8289 | 2000 | 0.2394          | 0.1849 |
+| 0.0113        | 4.2433 | 3000 | 0.2729          | 0.1722 |
+| 0.0036        | 5.6577 | 4000 | 0.3004          | 0.1705 |
+| 0.0012        | 7.0721 | 5000 | 0.3280          | 0.1676 |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

generation_config.json

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+}