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README.md
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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: gopdatastt_add_transformer
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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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# gopdatastt_add_transformer
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0920
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- Wer: 0.1617
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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: 30
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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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| 3.1709 | 1.05 | 500 | 0.1453 | 0.2194 |
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| 0.3131 | 2.11 | 1000 | 0.1094 | 0.2055 |
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| 0.276 | 3.16 | 1500 | 0.1198 | 0.1998 |
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| 0.2416 | 4.21 | 2000 | 0.1873 | 0.2026 |
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| 0.2093 | 5.26 | 2500 | 0.1392 | 0.1974 |
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| 0.1987 | 6.32 | 3000 | 0.1123 | 0.1944 |
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| 0.1714 | 7.37 | 3500 | 0.1089 | 0.1890 |
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| 0.1634 | 8.42 | 4000 | 0.1007 | 0.1863 |
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| 0.1459 | 9.47 | 4500 | 0.1340 | 0.1864 |
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| 0.1461 | 10.53 | 5000 | 0.1016 | 0.1874 |
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| 0.1316 | 11.58 | 5500 | 0.1110 | 0.1891 |
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| 0.1318 | 12.63 | 6000 | 0.0942 | 0.1855 |
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| 0.1084 | 13.68 | 6500 | 0.0992 | 0.1827 |
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| 0.1064 | 14.74 | 7000 | 0.1010 | 0.1801 |
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| 0.1059 | 15.79 | 7500 | 0.1173 | 0.1834 |
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| 0.094 | 16.84 | 8000 | 0.1096 | 0.1815 |
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| 0.0918 | 17.89 | 8500 | 0.1046 | 0.1780 |
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| 0.0874 | 18.95 | 9000 | 0.1103 | 0.1788 |
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| 0.0813 | 20.0 | 9500 | 0.1065 | 0.1768 |
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| 0.0753 | 21.05 | 10000 | 0.0997 | 0.1747 |
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| 0.0729 | 22.11 | 10500 | 0.1053 | 0.1748 |
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| 0.0655 | 23.16 | 11000 | 0.1042 | 0.1726 |
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| 0.0647 | 24.21 | 11500 | 0.0960 | 0.1746 |
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| 0.0581 | 25.26 | 12000 | 0.1060 | 0.1733 |
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| 0.0573 | 26.32 | 12500 | 0.0972 | 0.1706 |
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| 0.0524 | 27.37 | 13000 | 0.0963 | 0.1725 |
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| 0.0577 | 28.42 | 13500 | 0.0920 | 0.1696 |
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| 0.0488 | 29.47 | 14000 | 0.0942 | 0.1686 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 2.5.1+cu121
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- Datasets 1.18.3
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- Tokenizers 0.20.3
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