End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper-large-v2.vi2
+  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-v2.vi2
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3148
+- Wer: 13.9211
+
+## 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: 250
+- training_steps: 3000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0284        | 2.66  | 500  | 0.2743          | 21.3778 |
+| 0.0047        | 5.32  | 1000 | 0.2707          | 16.1299 |
+| 0.0007        | 7.98  | 1500 | 0.2929          | 12.4846 |
+| 0.0004        | 10.64 | 2000 | 0.3040          | 13.3418 |
+| 0.0003        | 13.3  | 2500 | 0.3125          | 13.9983 |
+| 0.0003        | 15.96 | 3000 | 0.3148          | 13.9211 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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