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--- |
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base_model: facebook/wav2vec2-large |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-large-sw-cv-100hr-v2 |
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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-large-sw-cv-100hr-v2 |
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This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6293 |
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- Model Preparation Time: 0.004 |
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- Wer: 0.3558 |
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- Cer: 0.1353 |
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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: 0.0007 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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_ratio: 0.6 |
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- num_epochs: 120 |
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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 | Model Preparation Time | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:| |
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| 3.5004 | 1.0 | 1040 | 0.7862 | 0.004 | 0.6822 | 0.1909 | |
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| 0.4704 | 2.0 | 2080 | 0.5245 | 0.004 | 0.4970 | 0.1335 | |
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| 0.3202 | 3.0 | 3120 | 0.4288 | 0.004 | 0.3956 | 0.1066 | |
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| 0.2551 | 4.0 | 4160 | 0.3800 | 0.004 | 0.3644 | 0.0962 | |
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| 0.2213 | 5.0 | 5200 | 0.3481 | 0.004 | 0.3358 | 0.0911 | |
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| 0.2005 | 6.0 | 6240 | 0.3241 | 0.004 | 0.3101 | 0.0839 | |
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| 0.1911 | 7.0 | 7280 | 0.3535 | 0.004 | 0.3283 | 0.0924 | |
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| 0.1854 | 8.0 | 8320 | 0.3161 | 0.004 | 0.3002 | 0.0843 | |
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| 0.1819 | 9.0 | 9360 | 0.3181 | 0.004 | 0.3233 | 0.0964 | |
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| 0.1788 | 10.0 | 10400 | 0.3099 | 0.004 | 0.3086 | 0.0832 | |
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| 0.1796 | 11.0 | 11440 | 0.3245 | 0.004 | 0.3011 | 0.0827 | |
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| 0.1805 | 12.0 | 12480 | 0.3068 | 0.004 | 0.2967 | 0.0845 | |
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| 0.1791 | 13.0 | 13520 | 0.3163 | 0.004 | 0.3076 | 0.0864 | |
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| 0.1812 | 14.0 | 14560 | 0.3336 | 0.004 | 0.3104 | 0.0867 | |
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| 0.1844 | 15.0 | 15600 | 0.3257 | 0.004 | 0.3117 | 0.0864 | |
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| 0.1884 | 16.0 | 16640 | 0.3440 | 0.004 | 0.3136 | 0.0886 | |
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| 0.1979 | 17.0 | 17680 | 0.3444 | 0.004 | 0.3172 | 0.0899 | |
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| 0.2058 | 18.0 | 18720 | 0.3286 | 0.004 | 0.3456 | 0.1092 | |
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| 0.2114 | 19.0 | 19760 | 0.3603 | 0.004 | 0.3358 | 0.0969 | |
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| 0.2229 | 20.0 | 20800 | 0.3658 | 0.004 | 0.3301 | 0.0954 | |
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| 0.2275 | 21.0 | 21840 | 0.3849 | 0.004 | 0.3729 | 0.1197 | |
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| 0.2351 | 22.0 | 22880 | 0.3753 | 0.004 | 0.3488 | 0.1011 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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