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--- |
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language: |
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- ev |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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: wav2vec2-large-xlsr-53 |
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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-xlsr-53 |
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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 the Evenki dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8728 |
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- Wer: 65.9678 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 500 |
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- num_epochs: 15 |
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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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| 8.8625 | 0.6279 | 100 | 4.7672 | 100.0 | |
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| 3.5933 | 1.2559 | 200 | 3.5125 | 100.0 | |
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| 3.4942 | 1.8838 | 300 | 3.4852 | 100.0 | |
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| 3.5053 | 2.5118 | 400 | 3.4885 | 100.0 | |
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| 3.2185 | 3.1397 | 500 | 2.8873 | 100.0 | |
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| 2.2076 | 3.7677 | 600 | 1.6237 | 99.9844 | |
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| 1.6129 | 4.3956 | 700 | 1.2754 | 92.5833 | |
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| 1.5995 | 5.0235 | 800 | 1.1585 | 84.6033 | |
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| 1.333 | 5.6515 | 900 | 1.0689 | 80.4882 | |
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| 1.2571 | 6.2794 | 1000 | 1.0283 | 77.4840 | |
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| 1.1675 | 6.9074 | 1100 | 0.9761 | 75.3716 | |
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| 1.1193 | 7.5353 | 1200 | 0.9367 | 73.3532 | |
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| 1.0054 | 8.1633 | 1300 | 0.9723 | 72.4300 | |
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| 1.0211 | 8.7912 | 1400 | 0.8911 | 70.4115 | |
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| 0.9408 | 9.4192 | 1500 | 0.9405 | 70.6775 | |
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| 0.9115 | 10.0471 | 1600 | 0.8998 | 68.2835 | |
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| 0.8533 | 10.6750 | 1700 | 0.9073 | 68.3461 | |
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| 0.7981 | 11.3030 | 1800 | 0.8838 | 67.8141 | |
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| 0.8154 | 11.9309 | 1900 | 0.8872 | 66.7345 | |
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| 0.7603 | 12.5589 | 2000 | 0.8681 | 66.9379 | |
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| 0.7711 | 13.1868 | 2100 | 0.8723 | 66.5154 | |
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| 0.6974 | 13.8148 | 2200 | 0.8634 | 66.1242 | |
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| 0.7224 | 14.4427 | 2300 | 0.8728 | 65.9678 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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