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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: whisper_tiny_fleurs |
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results: [] |
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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_tiny_fleurs |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the /home/investigacion/disco4TB/workspace_pablo/firvox_whisper_research/finetunnig/dataset/dataset_parquet/dataset_1000x6_noFirVox_correctedpaths.parquet dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9658 |
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- Accuracy: 0.7744 |
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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: 16 |
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- eval_batch_size: 32 |
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- seed: 0 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 64 |
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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_ratio: 0.1 |
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- num_epochs: 1.0 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.0287 | 1.0 | 80 | 0.9658 | 0.7744 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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