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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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datasets: |
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- kensho/spgispeech |
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widget: |
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- example_title: Finance Speech |
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src: https://drive.google.com/uc?id=151bzDnN_f0Dfjjrg36nI97tXM39t5Ka8 |
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model-index: |
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- name: wav2vec2-base-finetuned-spgispeech-dev |
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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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# wav2vec2-base-finetuned-spgispeech-dev |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [kensho/spgispeech](https://huggingface.co/datasets/kensho/spgispeech) dev dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2897 |
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- Wer: 0.1508 |
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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: 16 |
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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: 50 |
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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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| 1.8285 | 2.22 | 1500 | 0.3361 | 0.2754 | |
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| 0.2582 | 4.44 | 3000 | 0.2643 | 0.2205 | |
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| 0.1697 | 6.66 | 4500 | 0.2467 | 0.2006 | |
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| 0.1314 | 8.88 | 6000 | 0.2711 | 0.1927 | |
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| 0.1084 | 11.09 | 7500 | 0.2521 | 0.1872 | |
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| 0.0922 | 13.31 | 9000 | 0.2588 | 0.1827 | |
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| 0.0818 | 15.53 | 10500 | 0.2572 | 0.1783 | |
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| 0.0712 | 17.75 | 12000 | 0.2720 | 0.1766 | |
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| 0.067 | 19.97 | 13500 | 0.2873 | 0.1751 | |
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| 0.0594 | 22.19 | 15000 | 0.2753 | 0.1704 | |
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| 0.0546 | 24.41 | 16500 | 0.2794 | 0.1694 | |
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| 0.0505 | 26.63 | 18000 | 0.2811 | 0.1665 | |
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| 0.0467 | 28.85 | 19500 | 0.2906 | 0.1657 | |
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| 0.0417 | 31.07 | 21000 | 0.3043 | 0.1661 | |
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| 0.0395 | 33.28 | 22500 | 0.3068 | 0.1627 | |
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| 0.0368 | 35.5 | 24000 | 0.3096 | 0.1617 | |
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| 0.0334 | 37.72 | 25500 | 0.3036 | 0.1581 | |
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| 0.0322 | 39.94 | 27000 | 0.2819 | 0.1564 | |
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| 0.0286 | 42.16 | 28500 | 0.2936 | 0.1544 | |
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| 0.0279 | 44.38 | 30000 | 0.2914 | 0.1534 | |
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| 0.0264 | 46.6 | 31500 | 0.2957 | 0.1519 | |
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| 0.0241 | 48.82 | 33000 | 0.2897 | 0.1508 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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