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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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base_model: openai/whisper-base |
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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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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper base Spanish Improved |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: es |
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split: test |
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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: 20.435869264920363 |
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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 base Spanish Improved |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3238 |
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- Wer: 20.4359 |
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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: 5e-06 |
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- train_batch_size: 16 |
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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: 500 |
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- training_steps: 8000 |
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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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| 0.3177 | 0.12 | 1000 | 0.3974 | 23.5886 | |
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| 0.294 | 0.25 | 2000 | 0.3681 | 22.2548 | |
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| 0.3409 | 0.38 | 3000 | 0.3512 | 21.6964 | |
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| 0.26 | 0.5 | 4000 | 0.3407 | 21.2621 | |
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| 0.3503 | 0.62 | 5000 | 0.3345 | 20.8259 | |
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| 0.3067 | 0.75 | 6000 | 0.3297 | 20.5207 | |
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| 0.2324 | 0.88 | 7000 | 0.3243 | 20.4956 | |
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| 0.3413 | 1.0 | 8000 | 0.3238 | 20.4359 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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