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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: torgo_xlsr_finetune_M03 |
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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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# torgo_xlsr_finetune_M03 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1905 |
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- Wer: 0.2097 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 20 |
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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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| 3.5007 | 0.85 | 1000 | 3.2973 | 1.0 | |
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| 2.2459 | 1.71 | 2000 | 1.9925 | 0.8829 | |
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| 0.9013 | 2.56 | 3000 | 1.1537 | 0.6138 | |
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| 0.6388 | 3.41 | 4000 | 1.2210 | 0.5017 | |
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| 0.5391 | 4.27 | 5000 | 1.2570 | 0.4032 | |
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| 0.4528 | 5.12 | 6000 | 1.1298 | 0.3718 | |
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| 0.3892 | 5.97 | 7000 | 1.1642 | 0.3090 | |
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| 0.3382 | 6.83 | 8000 | 1.0970 | 0.3149 | |
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| 0.3279 | 7.68 | 9000 | 1.1686 | 0.3107 | |
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| 0.2816 | 8.53 | 10000 | 1.3912 | 0.3107 | |
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| 0.2667 | 9.39 | 11000 | 1.2643 | 0.2776 | |
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| 0.2517 | 10.24 | 12000 | 1.2157 | 0.2504 | |
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| 0.2312 | 11.09 | 13000 | 1.2624 | 0.2640 | |
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| 0.2239 | 11.95 | 14000 | 1.2676 | 0.2640 | |
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| 0.1849 | 12.8 | 15000 | 1.1427 | 0.2623 | |
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| 0.1841 | 13.65 | 16000 | 1.2277 | 0.2547 | |
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| 0.1793 | 14.51 | 17000 | 1.3833 | 0.2572 | |
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| 0.1704 | 15.36 | 18000 | 1.3813 | 0.2691 | |
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| 0.1688 | 16.21 | 19000 | 1.3418 | 0.2589 | |
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| 0.1527 | 17.06 | 20000 | 1.2787 | 0.2343 | |
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| 0.1304 | 17.92 | 21000 | 1.2078 | 0.2190 | |
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| 0.1332 | 18.77 | 22000 | 1.2041 | 0.2105 | |
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| 0.1253 | 19.62 | 23000 | 1.1905 | 0.2097 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.3 |
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