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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: None |
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metrics: |
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- type: wer |
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value: 0.1421388512860182 |
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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: 0.3440 |
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- Combined Wer: 0.2231 |
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- F1 Score: 0.5368 |
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- Label F1: 0.6908 |
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- Wer: 0.1421 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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 | Combined Wer | F1 Score | Label F1 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------:|:--------:|:------:| |
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| 1.1583 | 0.1 | 500 | 1.0361 | 0.3217 | 0.0746 | 0.1415 | 0.2067 | |
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| 0.4069 | 0.2 | 1000 | 0.4111 | 0.2203 | 0.4223 | 0.5940 | 0.1235 | |
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| 0.3708 | 0.3 | 1500 | 0.3768 | 0.2201 | 0.4609 | 0.6267 | 0.1295 | |
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| 0.3512 | 0.4 | 2000 | 0.3624 | 0.2223 | 0.5142 | 0.6835 | 0.1359 | |
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| 0.3411 | 0.5 | 2500 | 0.3543 | 0.2204 | 0.5225 | 0.6883 | 0.1374 | |
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| 0.3313 | 1.02 | 3000 | 0.3492 | 0.2235 | 0.5193 | 0.6808 | 0.1398 | |
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| 0.3252 | 1.12 | 3500 | 0.3459 | 0.2251 | 0.5333 | 0.6893 | 0.1436 | |
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| 0.3293 | 1.22 | 4000 | 0.3447 | 0.2237 | 0.5325 | 0.6860 | 0.1416 | |
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| 0.321 | 1.32 | 4500 | 0.3443 | 0.2238 | 0.5366 | 0.6905 | 0.1425 | |
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| 0.3223 | 1.42 | 5000 | 0.3440 | 0.2231 | 0.5368 | 0.6908 | 0.1421 | |
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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 |
