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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- automatic-speech-recognition |
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- BembaSpeech |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-bem-bl |
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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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# w2v-bert-bem-bl |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the BEMBASPEECH - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2136 |
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- Wer: 0.4539 |
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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: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 500 |
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- num_epochs: 10.0 |
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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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| 0.5344 | 0.7027 | 500 | 0.5448 | 0.7379 | |
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| 0.4242 | 1.4055 | 1000 | 0.3055 | 0.6025 | |
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| 0.3603 | 2.1082 | 1500 | 0.2693 | 0.5385 | |
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| 0.3144 | 2.8110 | 2000 | 0.2683 | 0.5529 | |
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| 0.2656 | 3.5137 | 2500 | 0.2472 | 0.5258 | |
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| 0.2311 | 4.2164 | 3000 | 0.2352 | 0.5026 | |
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| 0.2106 | 4.9192 | 3500 | 0.2327 | 0.5003 | |
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| 0.1816 | 5.6219 | 4000 | 0.2298 | 0.4987 | |
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| 0.1432 | 6.3247 | 4500 | 0.2178 | 0.4686 | |
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| 0.1431 | 7.0274 | 5000 | 0.2172 | 0.4747 | |
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| 0.1069 | 7.7301 | 5500 | 0.2136 | 0.4539 | |
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| 0.0767 | 8.4329 | 6000 | 0.2270 | 0.4403 | |
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| 0.0667 | 9.1356 | 6500 | 0.2375 | 0.4385 | |
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| 0.0468 | 9.8384 | 7000 | 0.2403 | 0.4353 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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