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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: w2v2-base-pretrained_lr5e-5_at0.8_da0.7 |
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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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# w2v2-base-pretrained_lr5e-5_at0.8_da0.7 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2042 |
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- Wer: 0.1884 |
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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: 5e-05 |
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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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- 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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- training_steps: 4000 |
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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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| 24.3422 | 7.81 | 250 | 5.6070 | 1.0 | |
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| 3.5981 | 15.62 | 500 | 3.2535 | 1.0 | |
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| 3.1121 | 23.44 | 750 | 3.1577 | 1.0 | |
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| 3.0596 | 31.25 | 1000 | 3.1214 | 1.0 | |
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| 3.0143 | 39.06 | 1250 | 2.9603 | 1.0 | |
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| 1.4861 | 46.88 | 1500 | 1.2406 | 0.4007 | |
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| 0.2223 | 54.69 | 1750 | 1.3926 | 0.2324 | |
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| 0.1147 | 62.5 | 2000 | 1.5275 | 0.2136 | |
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| 0.0775 | 70.31 | 2250 | 1.8277 | 0.1986 | |
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| 0.0601 | 78.12 | 2500 | 1.9747 | 0.1944 | |
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| 0.0479 | 85.94 | 2750 | 2.0632 | 0.1909 | |
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| 0.042 | 93.75 | 3000 | 2.1333 | 0.1991 | |
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| 0.0353 | 101.56 | 3250 | 2.1743 | 0.1982 | |
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| 0.0315 | 109.38 | 3500 | 2.1585 | 0.1939 | |
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| 0.0274 | 117.19 | 3750 | 2.1521 | 0.1914 | |
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| 0.0279 | 125.0 | 4000 | 2.2042 | 0.1884 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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