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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: 0.17739223993006523 |
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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: 0.2734 |
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- Wer Ortho: 0.2102 |
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- Wer: 0.1774 |
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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: 2e-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: 16 |
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- total_train_batch_size: 32 |
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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: 7 |
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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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| 0.1809 | 1.0 | 274 | 0.2244 | 0.2261 | 0.1947 | |
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| 0.0977 | 2.0 | 549 | 0.2306 | 0.2204 | 0.1856 | |
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| 0.0594 | 3.0 | 824 | 0.2332 | 0.2137 | 0.1814 | |
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| 0.0454 | 4.0 | 1099 | 0.2667 | 0.2315 | 0.1985 | |
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| 0.028 | 5.0 | 1374 | 0.2579 | 0.2151 | 0.1822 | |
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| 0.022 | 6.0 | 1649 | 0.2674 | 0.2188 | 0.1863 | |
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| 0.0202 | 6.98 | 1918 | 0.2734 | 0.2102 | 0.1774 | |
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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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