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update model card README.md
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README.md
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---
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language:
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- el
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: whisper-large-v2-greek
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: FLEURS
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type: google/fleurs
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config: el_gr
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split: test
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args: el_gr
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metrics:
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- name: Wer
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type: wer
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value: 1.0564819086535293
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# whisper-large-v2-greek
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the FLEURS dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2061
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- Wer Ortho: 1.0424
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- Wer: 1.0565
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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| 0.1416 | 1.0 | 217 | 0.1611 | 1.2560 | 1.2638 |
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| 0.0617 | 2.0 | 435 | 0.1612 | 1.1956 | 1.1930 |
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| 0.027 | 3.0 | 653 | 0.1716 | 1.6495 | 1.6518 |
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| 0.0155 | 4.0 | 871 | 0.1812 | 1.2816 | 1.2878 |
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| 0.0114 | 5.0 | 1088 | 0.1792 | 1.0087 | 1.0071 |
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| 0.0085 | 6.0 | 1306 | 0.1891 | 0.9757 | 0.9971 |
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| 0.0073 | 7.0 | 1524 | 0.2017 | 1.0040 | 1.0225 |
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| 0.0062 | 8.0 | 1742 | 0.1980 | 1.0737 | 1.0779 |
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| 0.0094 | 9.0 | 1959 | 0.2103 | 0.8469 | 0.8459 |
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| 0.0039 | 9.97 | 2170 | 0.2061 | 1.0424 | 1.0565 |
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### Framework versions
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- Transformers 4.30.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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