End of training

README.md

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+---
+language:
+- zh
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- generated_from_trainer
+datasets:
+- LeoKuo49/Amitabha_all
+model-index:
+- name: Whisper-finetune_all
+  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_all
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Amitabha_all dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0002
+- Cer: 0.1505
+
+## 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: 8
+- 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: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Cer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 0.0581        | 3.1056  | 1000 | 0.0515          | 6.2281 |
+| 0.0132        | 6.2112  | 2000 | 0.0075          | 2.8061 |
+| 0.0009        | 9.3168  | 3000 | 0.0006          | 0.3260 |
+| 0.0001        | 12.4224 | 4000 | 0.0002          | 0.1505 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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+}

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