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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: gopdataset_base_fadam |
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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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# gopdataset_base_fadam |
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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: 0.1001 |
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- Wer: 0.1662 |
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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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| 4.9033 | 1.05 | 500 | 3.0006 | 1.0 | |
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| 2.1655 | 2.11 | 1000 | 0.3024 | 0.3575 | |
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| 0.582 | 3.16 | 1500 | 0.2045 | 0.2566 | |
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| 0.3618 | 4.21 | 2000 | 0.1377 | 0.2188 | |
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| 0.3297 | 5.26 | 2500 | 0.1551 | 0.2232 | |
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| 0.2847 | 6.32 | 3000 | 0.1742 | 0.2486 | |
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| 0.2488 | 7.37 | 3500 | 0.2328 | 0.2036 | |
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| 0.1996 | 8.42 | 4000 | 0.1379 | 0.2079 | |
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| 0.2165 | 9.47 | 4500 | 0.1183 | 0.1924 | |
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| 0.189 | 10.53 | 5000 | 0.1295 | 0.1956 | |
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| 0.1817 | 11.58 | 5500 | 0.1198 | 0.1888 | |
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| 0.1682 | 12.63 | 6000 | 0.1270 | 0.1887 | |
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| 0.1246 | 13.68 | 6500 | 0.1211 | 0.1867 | |
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| 0.1442 | 14.74 | 7000 | 0.1301 | 0.1805 | |
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| 0.1732 | 15.79 | 7500 | 0.1107 | 0.1801 | |
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| 0.1142 | 16.84 | 8000 | 0.1096 | 0.1848 | |
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| 0.1485 | 17.89 | 8500 | 0.1075 | 0.1790 | |
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| 0.1037 | 18.95 | 9000 | 0.1109 | 0.1778 | |
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| 0.1155 | 20.0 | 9500 | 0.1120 | 0.1736 | |
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| 0.1162 | 21.05 | 10000 | 0.1053 | 0.1740 | |
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| 0.0874 | 22.11 | 10500 | 0.1157 | 0.1739 | |
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| 0.0797 | 23.16 | 11000 | 0.1128 | 0.1735 | |
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| 0.0726 | 24.21 | 11500 | 0.1089 | 0.1745 | |
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| 0.0691 | 25.26 | 12000 | 0.1084 | 0.1696 | |
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| 0.0677 | 26.32 | 12500 | 0.1059 | 0.1696 | |
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| 0.0582 | 27.37 | 13000 | 0.1065 | 0.1696 | |
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| 0.0669 | 28.42 | 13500 | 0.1001 | 0.1701 | |
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| 0.0956 | 29.47 | 14000 | 0.1017 | 0.1687 | |
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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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