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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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metrics: |
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- wer |
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model-index: |
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- name: assis |
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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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# assis |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3440 |
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- Wer: 1 |
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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: 1e-05 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 3000 |
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- training_steps: 5000 |
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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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| 16.8292 | 1.56 | 100 | 16.7197 | 1 | |
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| 15.1534 | 3.12 | 200 | 14.3410 | 1 | |
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| 10.7755 | 4.69 | 300 | 9.9820 | 1 | |
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| 6.4859 | 6.25 | 400 | 6.1913 | 1 | |
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| 4.0464 | 7.81 | 500 | 3.8280 | 1 | |
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| 3.3418 | 9.38 | 600 | 3.2733 | 1 | |
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| 3.217 | 10.94 | 700 | 3.1409 | 1 | |
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| 3.0927 | 12.5 | 800 | 3.0469 | 1 | |
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| 3.0235 | 14.06 | 900 | 3.0015 | 1 | |
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| 2.9902 | 15.62 | 1000 | 2.9748 | 1 | |
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| 2.945 | 17.19 | 1100 | 2.9550 | 1 | |
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| 2.9293 | 18.75 | 1200 | 2.9262 | 1 | |
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| 2.9139 | 20.31 | 1300 | 2.9230 | 1 | |
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| 2.9084 | 21.88 | 1400 | 2.9067 | 1 | |
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| 2.8941 | 23.44 | 1500 | 2.9077 | 1 | |
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| 2.8883 | 25.0 | 1600 | 2.8858 | 1 | |
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| 2.872 | 26.56 | 1700 | 2.8709 | 1 | |
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| 2.8641 | 28.12 | 1800 | 2.8587 | 1 | |
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| 2.8548 | 29.69 | 1900 | 2.8537 | 1 | |
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| 2.8396 | 31.25 | 2000 | 2.8371 | 1 | |
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| 2.7043 | 32.81 | 2100 | 2.6063 | 1 | |
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| 2.3905 | 34.38 | 2200 | 2.2233 | 1 | |
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| 1.9862 | 35.94 | 2300 | 1.7478 | 1 | |
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| 1.5463 | 37.5 | 2400 | 1.3176 | 1 | |
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| 1.218 | 39.06 | 2500 | 0.9948 | 1 | |
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| 0.9606 | 40.62 | 2600 | 0.7820 | 1 | |
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| 0.7923 | 42.19 | 2700 | 0.6577 | 1 | |
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| 0.6811 | 43.75 | 2800 | 0.5650 | 1 | |
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| 0.5927 | 45.31 | 2900 | 0.5204 | 1 | |
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| 0.5449 | 46.88 | 3000 | 0.4857 | 1 | |
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| 0.4876 | 48.44 | 3100 | 0.4526 | 1 | |
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| 0.4646 | 50.0 | 3200 | 0.4281 | 1 | |
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| 0.4374 | 51.56 | 3300 | 0.4376 | 1 | |
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| 0.3952 | 53.12 | 3400 | 0.4075 | 1 | |
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| 0.3952 | 54.69 | 3500 | 0.3937 | 1 | |
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| 0.3558 | 56.25 | 3600 | 0.3875 | 1 | |
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| 0.3527 | 57.81 | 3700 | 0.3775 | 1 | |
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| 0.3349 | 59.38 | 3800 | 0.3701 | 1 | |
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| 0.3264 | 60.94 | 3900 | 0.3576 | 1 | |
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| 0.3108 | 62.5 | 4000 | 0.3644 | 1 | |
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| 0.3104 | 64.06 | 4100 | 0.3548 | 1 | |
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| 0.3012 | 65.62 | 4200 | 0.3510 | 1 | |
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| 0.3027 | 67.19 | 4300 | 0.3486 | 1 | |
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| 0.2967 | 68.75 | 4400 | 0.3431 | 1 | |
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| 0.2892 | 70.31 | 4500 | 0.3391 | 1 | |
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| 0.296 | 71.88 | 4600 | 0.3427 | 1 | |
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| 0.2821 | 73.44 | 4700 | 0.3469 | 1 | |
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| 0.2701 | 75.0 | 4800 | 0.3428 | 1 | |
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| 0.2825 | 76.56 | 4900 | 0.3426 | 1 | |
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| 0.2549 | 78.12 | 5000 | 0.3440 | 1 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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