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Model: mikr/whisper-large-v3-czech-cv13
Source: Original Platform

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: openai/whisper-large-v3
+  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. -->
+
+# openai/whisper-large-v3
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1283
+- Wer: 0.0789
+
+## 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: 62
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- 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    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.0138        | 2.24  | 1000 | 0.0962          | 0.0863 |
+| 0.004         | 4.48  | 2000 | 0.1117          | 0.0844 |
+| 0.0015        | 6.73  | 3000 | 0.1178          | 0.0807 |
+| 0.0004        | 8.97  | 4000 | 0.1219          | 0.0792 |
+| 0.0002        | 11.21 | 5000 | 0.1283          | 0.0789 |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.0.0+cu117
+- Datasets 2.14.6
+- Tokenizers 0.14.1