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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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metrics: |
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- wer |
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model-index: |
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- name: adapter_freezed_base_const_lr_1-e3 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: 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: hy-AM |
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split: test |
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args: hy-AM |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.9564916295314947 |
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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_freezed_base_const_lr_1-e3 |
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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: 1.0297 |
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- Wer: 0.9565 |
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- Cer: 0.2641 |
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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: 0.001 |
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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: constant |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| 0.856 | 1.5385 | 500 | 0.9286 | 0.9535 | 0.2798 | |
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| 0.7189 | 3.0769 | 1000 | 0.8544 | 0.9296 | 0.2557 | |
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| 0.6114 | 4.6154 | 1500 | 0.9302 | 0.9596 | 0.2675 | |
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| 0.4397 | 6.1538 | 2000 | 0.9972 | 0.9294 | 0.2585 | |
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| 0.4507 | 7.6923 | 2500 | 0.9594 | 0.9363 | 0.2589 | |
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| 0.3154 | 9.2308 | 3000 | 1.0297 | 0.9565 | 0.2641 | |
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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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