End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-large
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper_large_finetune_Formosa
+  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_finetune_Formosa
+
+This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Formosa dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1572
+- Wer: 9.8143
+
+## 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: 2000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.2883        | 0.1018 | 500  | 0.1850          | 13.1693 |
+| 0.2687        | 0.2035 | 1000 | 0.1702          | 10.7376 |
+| 0.2417        | 0.3053 | 1500 | 0.1626          | 10.1341 |
+| 0.2628        | 0.4070 | 2000 | 0.1572          | 9.8143  |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 1.13.1+cu116
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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