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--- |
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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: qmeeus/whisper-small-multilingual-spoken-ner-pipeline-step-1 |
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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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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: facebook/voxpopuli |
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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: 0.09799520086694016 |
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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 |
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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: 0.2264 |
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- F1 Score: 0.6872 |
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- Label F1: 0.8325 |
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- Wer: 0.0980 |
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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: 8 |
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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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| 0.2746 | 0.36 | 200 | 0.2602 | 0.6565 | 0.8343 | 0.1090 | |
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| 0.2481 | 0.71 | 400 | 0.2465 | 0.6578 | 0.8348 | 0.1022 | |
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| 0.2385 | 1.07 | 600 | 0.2410 | 0.6685 | 0.8323 | 0.1048 | |
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| 0.2316 | 1.43 | 800 | 0.2374 | 0.6724 | 0.8317 | 0.1022 | |
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| 0.2291 | 1.79 | 1000 | 0.2348 | 0.6698 | 0.8292 | 0.0968 | |
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| 0.2205 | 2.14 | 1200 | 0.2334 | 0.6745 | 0.8339 | 0.0964 | |
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| 0.2211 | 2.5 | 1400 | 0.2319 | 0.6729 | 0.8327 | 0.0961 | |
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| 0.2163 | 2.86 | 1600 | 0.2305 | 0.6732 | 0.8300 | 0.0981 | |
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| 0.2108 | 3.22 | 1800 | 0.2299 | 0.6734 | 0.8328 | 0.0954 | |
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| 0.2104 | 3.57 | 2000 | 0.2297 | 0.6792 | 0.8369 | 0.0992 | |
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| 0.2124 | 3.93 | 2200 | 0.2279 | 0.6782 | 0.8346 | 0.0945 | |
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| 0.2027 | 4.29 | 2400 | 0.2279 | 0.6790 | 0.8336 | 0.0944 | |
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| 0.2055 | 4.65 | 2600 | 0.2275 | 0.6832 | 0.8347 | 0.0949 | |
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| 0.209 | 5.0 | 2800 | 0.2269 | 0.6822 | 0.8336 | 0.0983 | |
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| 0.2017 | 5.36 | 3000 | 0.2272 | 0.6835 | 0.8346 | 0.0979 | |
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| 0.2029 | 5.72 | 3200 | 0.2266 | 0.6819 | 0.8321 | 0.0966 | |
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| 0.201 | 6.08 | 3400 | 0.2266 | 0.6800 | 0.8327 | 0.0978 | |
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| 0.1985 | 6.43 | 3600 | 0.2267 | 0.6856 | 0.8335 | 0.0995 | |
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| 0.1996 | 6.79 | 3800 | 0.2265 | 0.6864 | 0.8343 | 0.0988 | |
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| 0.197 | 7.15 | 4000 | 0.2264 | 0.6843 | 0.8347 | 0.0986 | |
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| 0.1985 | 7.51 | 4200 | 0.2264 | 0.6838 | 0.8352 | 0.0985 | |
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| 0.1999 | 7.86 | 4400 | 0.2263 | 0.6861 | 0.8346 | 0.0978 | |
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| 0.1963 | 8.22 | 4600 | 0.2264 | 0.6864 | 0.8318 | 0.0978 | |
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| 0.1977 | 8.58 | 4800 | 0.2264 | 0.6875 | 0.8329 | 0.0979 | |
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| 0.1961 | 8.94 | 5000 | 0.2264 | 0.6872 | 0.8325 | 0.0980 | |
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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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