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--- |
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library_name: transformers |
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language: |
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- da |
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license: apache-2.0 |
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base_model: openai/whisper-large |
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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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- alexandrainst/ftspeech |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper small FTSpeech - Julie |
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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: ftspeech |
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type: alexandrainst/ftspeech |
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args: 'split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 19.463820660777202 |
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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 FTSpeech - Julie |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the ftspeech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2781 |
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- Wer: 19.4638 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 200 |
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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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| 0.4214 | 0.0080 | 500 | 0.4317 | 26.8590 | |
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| 0.3568 | 0.0161 | 1000 | 0.3763 | 24.5151 | |
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| 0.3443 | 0.0241 | 1500 | 0.3443 | 23.0618 | |
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| 0.3218 | 0.0321 | 2000 | 0.3275 | 22.0048 | |
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| 0.2851 | 0.0402 | 2500 | 0.3139 | 21.2409 | |
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| 0.2638 | 0.0482 | 3000 | 0.3021 | 20.4187 | |
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| 0.2515 | 0.0562 | 3500 | 0.2943 | 20.2420 | |
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| 0.2692 | 0.0643 | 4000 | 0.2864 | 19.9020 | |
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| 0.2503 | 0.0723 | 4500 | 0.2806 | 19.6671 | |
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| 0.2396 | 0.0803 | 5000 | 0.2781 | 19.4638 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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