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--- |
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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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- common_voice_11_0 |
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metrics: |
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- wer |
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base_model: juancopi81/whisper-medium-es-train-valid |
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model-index: |
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- name: juancopi81/whisper-medium-es-train-valid |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: 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: es |
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metrics: |
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- type: wer |
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value: 6.15482563276337 |
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name: Wer |
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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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# juancopi81/whisper-medium-es-train-valid |
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This model is a fine-tuned version of [juancopi81/whisper-medium-es-train-valid](https://huggingface.co/juancopi81/whisper-medium-es-train-valid) 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: 0.2227 |
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- Wer: 6.1548 |
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Using the script provided in the Whisper Sprint (Dec. 2022) the models achieves these results on the evaluation sets (WER): |
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- google/fleurs: 6.94 |
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- mozilla-foundation/common_voice_11_0: XXXX |
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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: 32 |
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- eval_batch_size: 16 |
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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: 5000 |
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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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| 0.0539 | 1.01 | 1000 | 0.2100 | 6.4465 | |
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| 0.0211 | 2.01 | 2000 | 0.2286 | 6.5082 | |
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| 0.0088 | 3.02 | 3000 | 0.2418 | 6.3848 | |
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| 0.0205 | 4.02 | 4000 | 0.2288 | 6.6603 | |
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| 0.1031 | 5.03 | 5000 | 0.2227 | 6.1548 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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