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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-large-v3-pt-1000h-ct2 |
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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: fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba |
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default |
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type: fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.11132023872721715 |
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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-large-v3-pt-1000h-ct2 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba default dataset. It was converted to the CTranslate2 format. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5576 |
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- Wer: 0.1113 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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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: 10000 |
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- training_steps: 82000 |
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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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| 0.2717 | 0.39 | 10000 | 0.4143 | 0.1341 | |
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| 0.2646 | 0.79 | 20000 | 0.4141 | 0.1284 | |
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| 0.2244 | 1.18 | 30000 | 0.5361 | 0.1253 | |
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| 0.2056 | 1.57 | 40000 | 0.4714 | 0.1223 | |
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| 0.2034 | 1.97 | 50000 | 0.4937 | 0.1195 | |
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| 0.1717 | 2.36 | 60000 | 0.5127 | 0.1178 | |
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| 0.1692 | 2.75 | 70000 | 0.6040 | 0.1146 | |
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| 0.121 | 3.15 | 80000 | 0.5361 | 0.1130 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.1.dev0 |
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- Tokenizers 0.15.2 |
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