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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: openai/whisper-small |
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datasets: |
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- facebook/voxpopuli |
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metrics: |
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- wer |
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model-index: |
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- name: WhisperForSpokenNER-end2end |
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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: facebook/voxpopuli de+es+fr+nl |
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type: facebook/voxpopuli |
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split: de+es+fr+nl |
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metrics: |
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- type: wer |
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value: 0.38886263390044107 |
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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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# WhisperForSpokenNER-end2end |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/voxpopuli de+es+fr+nl dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3381 |
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- Wer: 0.3889 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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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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| 2.3436 | 0.36 | 200 | 1.8791 | 0.8871 | |
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| 1.1682 | 0.71 | 400 | 1.0307 | 0.5048 | |
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| 0.7321 | 1.07 | 600 | 0.6300 | 0.3665 | |
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| 0.4564 | 1.43 | 800 | 0.4381 | 0.3515 | |
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| 0.4095 | 1.79 | 1000 | 0.4027 | 0.3330 | |
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| 0.3813 | 2.14 | 1200 | 0.3847 | 0.3360 | |
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| 0.3667 | 2.5 | 1400 | 0.3734 | 0.3392 | |
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| 0.3583 | 2.86 | 1600 | 0.3649 | 0.3490 | |
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| 0.3454 | 3.22 | 1800 | 0.3588 | 0.3572 | |
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| 0.3422 | 3.57 | 2000 | 0.3537 | 0.3705 | |
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| 0.3371 | 3.93 | 2200 | 0.3503 | 0.3811 | |
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| 0.3291 | 4.29 | 2400 | 0.3475 | 0.3678 | |
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| 0.324 | 4.65 | 2600 | 0.3451 | 0.3670 | |
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| 0.3262 | 5.0 | 2800 | 0.3431 | 0.3710 | |
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| 0.3168 | 5.36 | 3000 | 0.3419 | 0.3847 | |
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| 0.3178 | 5.72 | 3200 | 0.3406 | 0.3833 | |
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| 0.3136 | 6.08 | 3400 | 0.3400 | 0.3853 | |
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| 0.3092 | 6.43 | 3600 | 0.3393 | 0.3896 | |
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| 0.3106 | 6.79 | 3800 | 0.3389 | 0.3900 | |
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| 0.3057 | 7.15 | 4000 | 0.3388 | 0.3803 | |
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| 0.3087 | 7.51 | 4200 | 0.3383 | 0.3941 | |
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| 0.308 | 7.86 | 4400 | 0.3382 | 0.3874 | |
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| 0.3036 | 8.22 | 4600 | 0.3381 | 0.3896 | |
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| 0.3087 | 8.58 | 4800 | 0.3380 | 0.3910 | |
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| 0.3079 | 8.94 | 5000 | 0.3381 | 0.3889 | |
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### Framework versions |
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- PEFT 0.7.1.dev0 |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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