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--- |
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base_model: facebook/w2v-bert-2.0 |
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datasets: |
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- common_voice_17_0 |
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library_name: transformers |
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license: mit |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: w2v-bert-2_6_datasets |
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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: common_voice_17_0 |
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type: common_voice_17_0 |
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config: ml |
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split: validation |
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args: ml |
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metrics: |
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- type: wer |
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value: 0.43922053819981444 |
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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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# w2v-bert-2_6_datasets |
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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 common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5077 |
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- Wer: 0.4392 |
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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: 16 |
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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: 32 |
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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 |
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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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| 1.1114 | 0.4038 | 600 | 0.6364 | 0.6514 | |
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| 0.1782 | 0.8075 | 1200 | 0.5620 | 0.6127 | |
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| 0.1374 | 1.2113 | 1800 | 0.4943 | 0.5654 | |
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| 0.1156 | 1.6151 | 2400 | 0.4415 | 0.5376 | |
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| 0.1068 | 2.0188 | 3000 | 0.4187 | 0.5249 | |
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| 0.0838 | 2.4226 | 3600 | 0.4778 | 0.5320 | |
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| 0.0834 | 2.8264 | 4200 | 0.4186 | 0.5091 | |
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| 0.0703 | 3.2301 | 4800 | 0.4538 | 0.5363 | |
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| 0.0636 | 3.6339 | 5400 | 0.4287 | 0.5314 | |
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| 0.0609 | 4.0377 | 6000 | 0.4013 | 0.4989 | |
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| 0.0462 | 4.4415 | 6600 | 0.4053 | 0.4964 | |
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| 0.047 | 4.8452 | 7200 | 0.4289 | 0.4766 | |
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| 0.0377 | 5.2490 | 7800 | 0.3875 | 0.4933 | |
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| 0.0352 | 5.6528 | 8400 | 0.3906 | 0.4881 | |
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| 0.033 | 6.0565 | 9000 | 0.4192 | 0.4667 | |
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| 0.0243 | 6.4603 | 9600 | 0.4113 | 0.4723 | |
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| 0.0244 | 6.8641 | 10200 | 0.4393 | 0.4708 | |
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| 0.0189 | 7.2678 | 10800 | 0.4255 | 0.4630 | |
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| 0.0167 | 7.6716 | 11400 | 0.4219 | 0.4646 | |
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| 0.0157 | 8.0754 | 12000 | 0.4398 | 0.4429 | |
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| 0.0107 | 8.4791 | 12600 | 0.4546 | 0.4507 | |
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| 0.0095 | 8.8829 | 13200 | 0.4949 | 0.4426 | |
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| 0.0072 | 9.2867 | 13800 | 0.4972 | 0.4473 | |
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| 0.0059 | 9.6904 | 14400 | 0.5077 | 0.4392 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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