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--- |
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license: cc0-1.0 |
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tags: |
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- automatic-speech-recognition |
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- marinone94/nst_sv |
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- generated_from_trainer |
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datasets: |
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- nst_sv |
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model-index: |
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- name: '' |
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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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# |
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This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MARINONE94/NST_SV - DISTANT_CHANNEL dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 1.0 |
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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: 0.00075 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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_ratio: 0.02 |
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- num_epochs: 2.0 |
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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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| 3.4039 | 0.05 | 100 | inf | 1.0 | |
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| 3.4396 | 0.11 | 200 | inf | 1.0 | |
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| 3.483 | 0.16 | 300 | inf | 1.0 | |
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| 3.5014 | 0.21 | 400 | inf | 1.0 | |
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| 3.331 | 0.27 | 500 | inf | 1.0 | |
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| 3.4809 | 0.32 | 600 | inf | 1.0 | |
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| 3.4678 | 0.37 | 700 | inf | 1.0 | |
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| 3.4596 | 0.43 | 800 | inf | 1.0 | |
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| 3.4644 | 0.48 | 900 | inf | 1.0 | |
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| 3.4671 | 0.53 | 1000 | inf | 1.0 | |
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| 3.6005 | 0.59 | 1100 | inf | 1.0 | |
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| 3.9182 | 0.64 | 1200 | inf | 1.0 | |
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| 3.6466 | 0.69 | 1300 | inf | 1.0 | |
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| 3.6932 | 0.75 | 1400 | inf | 1.0 | |
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| 3.7939 | 0.8 | 1500 | inf | 1.0 | |
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| 3.9284 | 0.85 | 1600 | inf | 1.0 | |
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| 3.7859 | 0.91 | 1700 | inf | 1.0 | |
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| 3.9363 | 0.96 | 1800 | inf | 1.0 | |
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| 3.7573 | 1.01 | 1900 | inf | 1.0 | |
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| 3.7553 | 1.07 | 2000 | inf | 1.0 | |
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| 3.7606 | 1.12 | 2100 | inf | 1.0 | |
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| 3.7514 | 1.17 | 2200 | inf | 1.0 | |
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| 3.7472 | 1.23 | 2300 | inf | 1.0 | |
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| 3.7478 | 1.28 | 2400 | inf | 1.0 | |
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| 3.7496 | 1.33 | 2500 | inf | 1.0 | |
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| 3.7513 | 1.39 | 2600 | inf | 1.0 | |
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| 3.7497 | 1.44 | 2700 | inf | 1.0 | |
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| 3.7539 | 1.49 | 2800 | inf | 1.0 | |
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| 3.7581 | 1.55 | 2900 | inf | 1.0 | |
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| 3.7572 | 1.6 | 3000 | inf | 1.0 | |
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| 3.7589 | 1.66 | 3100 | inf | 1.0 | |
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| 3.7592 | 1.71 | 3200 | inf | 1.0 | |
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| 3.7531 | 1.76 | 3300 | inf | 1.0 | |
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| 3.7567 | 1.82 | 3400 | inf | 1.0 | |
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| 3.7613 | 1.87 | 3500 | inf | 1.0 | |
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| 3.7516 | 1.92 | 3600 | inf | 1.0 | |
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| 3.7581 | 1.98 | 3700 | inf | 1.0 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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