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--- |
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base_model: qmeeus/whisper-small-multilingual-spoken-ner-pipeline-step-1 |
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tags: |
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- generated_from_trainer |
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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 |
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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: facebook/voxpopuli de+es+fr+nl |
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type: facebook/voxpopuli |
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config: de+es+fr+nl |
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split: train |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.10856103413576902 |
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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 |
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This model is a fine-tuned version of [/esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner](https://huggingface.co.//esat/audioslave/qmeeus/exp/whisper_slu/train/whisper-small-spoken-ner) 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: 0.0444 |
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- F1 Score: 0.6098 |
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- Label F1: 0.8369 |
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- Wer: 0.1086 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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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: 100 |
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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 | F1 Score | Label F1 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:| |
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| 0.0433 | 0.36 | 200 | 0.0523 | 0.6251 | 0.8320 | 0.1043 | |
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| 0.0391 | 0.71 | 400 | 0.0504 | 0.6207 | 0.8346 | 0.1047 | |
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| 0.0381 | 1.07 | 600 | 0.0496 | 0.6142 | 0.8322 | 0.1065 | |
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| 0.0374 | 1.43 | 800 | 0.0484 | 0.6158 | 0.8360 | 0.1071 | |
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| 0.0374 | 1.79 | 1000 | 0.0474 | 0.6155 | 0.8370 | 0.1069 | |
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| 0.0342 | 2.14 | 1200 | 0.0474 | 0.6118 | 0.8362 | 0.1077 | |
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| 0.0362 | 2.5 | 1400 | 0.0468 | 0.6138 | 0.8375 | 0.1079 | |
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| 0.0351 | 2.86 | 1600 | 0.0461 | 0.6102 | 0.8361 | 0.1082 | |
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| 0.0339 | 3.22 | 1800 | 0.0466 | 0.6111 | 0.8388 | 0.1079 | |
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| 0.0323 | 3.57 | 2000 | 0.0467 | 0.6168 | 0.8419 | 0.1088 | |
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| 0.0338 | 3.93 | 2200 | 0.0457 | 0.6093 | 0.8426 | 0.1086 | |
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| 0.032 | 4.29 | 2400 | 0.0452 | 0.6090 | 0.8398 | 0.1085 | |
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| 0.0307 | 4.65 | 2600 | 0.0451 | 0.6139 | 0.8422 | 0.1086 | |
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| 0.0321 | 5.0 | 2800 | 0.0452 | 0.6116 | 0.8398 | 0.1083 | |
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| 0.0313 | 5.36 | 3000 | 0.0448 | 0.6116 | 0.8404 | 0.1092 | |
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| 0.0309 | 5.72 | 3200 | 0.0449 | 0.6109 | 0.8402 | 0.1083 | |
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| 0.0305 | 6.08 | 3400 | 0.0448 | 0.6086 | 0.8402 | 0.1083 | |
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| 0.0301 | 6.43 | 3600 | 0.0447 | 0.6116 | 0.8375 | 0.1081 | |
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| 0.03 | 6.79 | 3800 | 0.0446 | 0.6103 | 0.8401 | 0.1087 | |
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| 0.0302 | 7.15 | 4000 | 0.0445 | 0.6120 | 0.8388 | 0.1084 | |
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| 0.0294 | 7.51 | 4200 | 0.0442 | 0.6132 | 0.8396 | 0.1086 | |
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| 0.03 | 7.86 | 4400 | 0.0444 | 0.6112 | 0.8382 | 0.1088 | |
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| 0.03 | 8.22 | 4600 | 0.0445 | 0.6109 | 0.8371 | 0.1087 | |
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| 0.0296 | 8.58 | 4800 | 0.0444 | 0.6117 | 0.8378 | 0.1084 | |
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| 0.0297 | 8.94 | 5000 | 0.0444 | 0.6098 | 0.8369 | 0.1086 | |
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### Framework versions |
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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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