83 lines
2.1 KiB
Markdown
83 lines
2.1 KiB
Markdown
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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: wu-kiot/whisper-small-am-fleurs
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_0
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metrics:
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- wer
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model-index:
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- name: whisper-small-fc-am
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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_17_0
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type: common_voice_17_0
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config: am
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split: None
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args: am
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metrics:
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- name: Wer
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type: wer
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value: 62.73062730627307
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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-fc-am
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This model is a fine-tuned version of [wu-kiot/whisper-small-am-fleurs](https://huggingface.co/wu-kiot/whisper-small-am-fleurs) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3756
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- Wer: 62.7306
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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-05
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 150
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- num_epochs: 5
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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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| 0.2866 | 1.0 | 44 | 0.2855 | 63.9958 |
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| 0.1582 | 2.0 | 88 | 0.2958 | 64.1539 |
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| 0.0885 | 3.0 | 132 | 0.3311 | 67.4222 |
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| 0.0793 | 4.0 | 176 | 0.3700 | 66.4207 |
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| 0.0375 | 5.0 | 220 | 0.3756 | 62.7306 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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