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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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- it
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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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- mozilla-foundation/common_voice_13_0
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metrics:
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- wer
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model-index:
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- name: whisper-large-v2-italian
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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: COMMON_VOICE_13_0
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type: mozilla-foundation/common_voice_13_0
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config: it
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split: test
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args: it
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metrics:
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- name: Wer
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type: wer
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value: 0.1066490153897071
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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-italian
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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 COMMON_VOICE_13_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2397
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- Wer Ortho: 0.1538
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- Wer: 0.1066
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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: 3e-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: 2
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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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| 0.2182 | 1.0 | 979 | 0.2368 | 0.1564 | 0.1070 |
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| 0.1192 | 2.0 | 1958 | 0.2397 | 0.1538 | 0.1066 |
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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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