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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: aradia-ctc-hubert-ft |
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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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# aradia-ctc-hubert-ft |
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This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6928 |
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- Wer: 0.3946 |
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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: 0.0003 |
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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: 2 |
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- total_train_batch_size: 64 |
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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: 500 |
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- num_epochs: 15.0 |
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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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| No log | 0.43 | 100 | 3.6934 | 1.0 | |
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| No log | 0.87 | 200 | 3.0763 | 1.0 | |
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| No log | 1.3 | 300 | 2.9737 | 1.0 | |
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| No log | 1.74 | 400 | 2.5734 | 1.0 | |
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| 5.0957 | 2.17 | 500 | 1.1900 | 0.9011 | |
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| 5.0957 | 2.61 | 600 | 0.9726 | 0.7572 | |
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| 5.0957 | 3.04 | 700 | 0.8960 | 0.6209 | |
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| 5.0957 | 3.48 | 800 | 0.7851 | 0.5515 | |
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| 5.0957 | 3.91 | 900 | 0.7271 | 0.5115 | |
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| 1.0312 | 4.35 | 1000 | 0.7053 | 0.4955 | |
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| 1.0312 | 4.78 | 1100 | 0.6823 | 0.4737 | |
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| 1.0312 | 5.22 | 1200 | 0.6768 | 0.4595 | |
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| 1.0312 | 5.65 | 1300 | 0.6635 | 0.4488 | |
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| 1.0312 | 6.09 | 1400 | 0.6602 | 0.4390 | |
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| 0.6815 | 6.52 | 1500 | 0.6464 | 0.4310 | |
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| 0.6815 | 6.95 | 1600 | 0.6455 | 0.4394 | |
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| 0.6815 | 7.39 | 1700 | 0.6630 | 0.4312 | |
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| 0.6815 | 7.82 | 1800 | 0.6521 | 0.4126 | |
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| 0.6815 | 8.26 | 1900 | 0.6282 | 0.4284 | |
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| 0.544 | 8.69 | 2000 | 0.6248 | 0.4178 | |
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| 0.544 | 9.13 | 2100 | 0.6510 | 0.4104 | |
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| 0.544 | 9.56 | 2200 | 0.6527 | 0.4013 | |
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| 0.544 | 10.0 | 2300 | 0.6511 | 0.4064 | |
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| 0.544 | 10.43 | 2400 | 0.6734 | 0.4061 | |
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| 0.4478 | 10.87 | 2500 | 0.6756 | 0.4145 | |
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| 0.4478 | 11.3 | 2600 | 0.6727 | 0.3990 | |
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| 0.4478 | 11.74 | 2700 | 0.6619 | 0.4007 | |
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| 0.4478 | 12.17 | 2800 | 0.6614 | 0.4019 | |
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| 0.4478 | 12.61 | 2900 | 0.6695 | 0.4004 | |
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| 0.3919 | 13.04 | 3000 | 0.6778 | 0.3966 | |
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| 0.3919 | 13.48 | 3100 | 0.6872 | 0.3971 | |
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| 0.3919 | 13.91 | 3200 | 0.6882 | 0.3945 | |
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| 0.3919 | 14.35 | 3300 | 0.6938 | 0.3937 | |
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| 0.3919 | 14.78 | 3400 | 0.6928 | 0.3946 | |
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### Framework versions |
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- Transformers 4.18.0.dev0 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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