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README.md
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---
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language:
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- ES
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license: apache-2.0
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tags:
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- hf-asr-leaderboard
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- generated_from_trainer
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datasets:
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- MINDS
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metrics:
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- wer
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model-index:
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- name: Whisper Small ES - ROGRANMAR
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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: minds
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type: MINDS
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config: null
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split: None
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args: 'config: ES, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 100.0
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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 Small ES - ROGRANMAR
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the minds dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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- Wer: 100.0
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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: 0.1
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- train_batch_size: 64
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1
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- training_steps: 40
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|
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| No log | 5.0 | 10 | 141.9978 | 1248.1793 |
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| No log | 10.0 | 20 | nan | 100.0 |
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| 77.0413 | 15.0 | 30 | nan | 100.0 |
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| 77.0413 | 20.0 | 40 | nan | 100.0 |
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### Framework versions
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- Transformers 4.29.0.dev0
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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