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--- |
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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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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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model-index: |
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- name: adapter_head_l15_to_l23_const_lr_1e-4 |
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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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# adapter_head_l15_to_l23_const_lr_1e-4 |
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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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- eval_loss: 1.9170 |
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- eval_wer: 0.9905 |
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- eval_cer: 0.2718 |
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- eval_runtime: 219.8282 |
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- eval_samples_per_second: 19.474 |
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- eval_steps_per_second: 2.438 |
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- epoch: 41.5385 |
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- step: 13500 |
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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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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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