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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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- precision |
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- recall |
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model-index: |
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- name: whisper-tiny-oshiwambo-speech |
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results: [] |
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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-tiny-oshiwambo-speech |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1409 |
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- Wer: 44.7619 |
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- Cer: 30.8962 |
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- Word Acc: 64.4444 |
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- Sent Acc: 2.8571 |
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- Precision: 0.6444 |
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- Recall: 0.5524 |
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- F1 Score: 0.5949 |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_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: 100 |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Word Acc | Sent Acc | Precision | Recall | F1 Score | |
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|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|:--------:|:--------:|:---------:|:------:|:--------:| |
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| 0.0098 | 117.65 | 1000 | 0.0976 | 37.1429 | 29.0094 | 66.6667 | 8.5714 | 0.6538 | 0.6476 | 0.6507 | |
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| 0.0105 | 235.29 | 2000 | 0.1061 | 41.9048 | 33.0189 | 63.6364 | 2.8571 | 0.6238 | 0.6 | 0.6117 | |
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| 0.0105 | 352.94 | 3000 | 0.1134 | 37.1429 | 26.8868 | 66.6667 | 5.7143 | 0.6667 | 0.6286 | 0.6471 | |
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| 0.0091 | 470.59 | 4000 | 0.1222 | 37.1429 | 25.7075 | 66.6667 | 5.7143 | 0.6667 | 0.6286 | 0.6471 | |
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| 0.0098 | 588.24 | 5000 | 0.1265 | 40.0 | 28.3019 | 65.625 | 2.8571 | 0.6562 | 0.6 | 0.6269 | |
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| 0.0094 | 705.88 | 6000 | 0.1314 | 42.8571 | 30.8962 | 64.5161 | 2.8571 | 0.6452 | 0.5714 | 0.6061 | |
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| 0.0093 | 823.53 | 7000 | 0.1366 | 42.8571 | 29.2453 | 64.5161 | 2.8571 | 0.6452 | 0.5714 | 0.6061 | |
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| 0.0094 | 941.18 | 8000 | 0.1360 | 45.7143 | 31.8396 | 63.3333 | 0.0 | 0.6333 | 0.5429 | 0.5846 | |
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| 0.01 | 1058.82 | 9000 | 0.1394 | 44.7619 | 30.8962 | 64.4444 | 2.8571 | 0.6444 | 0.5524 | 0.5949 | |
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| 0.0087 | 1176.47 | 10000 | 0.1409 | 44.7619 | 30.8962 | 64.4444 | 2.8571 | 0.6444 | 0.5524 | 0.5949 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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