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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec_asr_swbd_10_epochs |
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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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# wav2vec_asr_swbd_10_epochs |
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This model is a fine-tuned version of [facebook/wav2vec2-large-robust-ft-swbd-300h](https://huggingface.co/facebook/wav2vec2-large-robust-ft-swbd-300h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Wer: 0.9627 |
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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: 0.0001 |
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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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- 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: 1000 |
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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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| 1.0682 | 0.22 | 5000 | 0.7383 | 0.4431 | |
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| 0.9143 | 0.44 | 10000 | 0.7182 | 0.4058 | |
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| 0.8905 | 0.66 | 15000 | 0.6291 | 0.3987 | |
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| 0.8354 | 0.87 | 20000 | 0.5976 | 0.3954 | |
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| 0.7749 | 1.09 | 25000 | 0.5773 | 0.3901 | |
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| 0.7336 | 1.31 | 30000 | 0.5812 | 0.3871 | |
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| 0.7314 | 1.53 | 35000 | 0.5802 | 0.3895 | |
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| 0.0 | 1.75 | 40000 | nan | 0.9627 | |
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| 0.0 | 1.97 | 45000 | nan | 0.9627 | |
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| 0.0 | 2.19 | 50000 | nan | 0.9627 | |
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| 0.0 | 2.4 | 55000 | nan | 0.9627 | |
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| 0.0 | 2.62 | 60000 | nan | 0.9627 | |
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| 0.0 | 2.84 | 65000 | nan | 0.9627 | |
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| 0.0 | 3.06 | 70000 | nan | 0.9627 | |
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| 0.0 | 3.28 | 75000 | nan | 0.9627 | |
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| 0.0 | 3.5 | 80000 | nan | 0.9627 | |
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| 0.0 | 3.72 | 85000 | nan | 0.9627 | |
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| 0.0 | 3.93 | 90000 | nan | 0.9627 | |
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| 0.0 | 4.15 | 95000 | nan | 0.9627 | |
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| 0.0 | 4.37 | 100000 | nan | 0.9627 | |
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| 0.0 | 4.59 | 105000 | nan | 0.9627 | |
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| 0.0 | 4.81 | 110000 | nan | 0.9627 | |
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| 0.0 | 5.03 | 115000 | nan | 0.9627 | |
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| 0.0 | 5.25 | 120000 | nan | 0.9627 | |
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| 0.0 | 5.46 | 125000 | nan | 0.9627 | |
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| 0.0 | 5.68 | 130000 | nan | 0.9627 | |
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| 0.0 | 5.9 | 135000 | nan | 0.9627 | |
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| 0.0 | 6.12 | 140000 | nan | 0.9627 | |
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| 0.0 | 6.34 | 145000 | nan | 0.9627 | |
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| 0.0 | 6.56 | 150000 | nan | 0.9627 | |
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| 0.0 | 6.78 | 155000 | nan | 0.9627 | |
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| 0.0 | 7.0 | 160000 | nan | 0.9627 | |
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| 0.0 | 7.21 | 165000 | nan | 0.9627 | |
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| 0.0 | 7.43 | 170000 | nan | 0.9627 | |
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| 0.0 | 7.65 | 175000 | nan | 0.9627 | |
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| 0.0 | 7.87 | 180000 | nan | 0.9627 | |
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| 0.0 | 8.09 | 185000 | nan | 0.9627 | |
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| 0.0 | 8.31 | 190000 | nan | 0.9627 | |
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| 0.0 | 8.53 | 195000 | nan | 0.9627 | |
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| 0.0 | 8.74 | 200000 | nan | 0.9627 | |
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| 0.0 | 8.96 | 205000 | nan | 0.9627 | |
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| 0.0 | 9.18 | 210000 | nan | 0.9627 | |
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| 0.0 | 9.4 | 215000 | nan | 0.9627 | |
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| 0.0 | 9.62 | 220000 | nan | 0.9627 | |
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| 0.0 | 9.84 | 225000 | nan | 0.9627 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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