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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_at0.4_da1 |
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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_at0.4_da1 |
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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: 1.4372 |
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- Wer: 0.1666 |
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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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| 18.4042 | 4.03 | 250 | 4.2497 | 1.0 | |
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| 3.3741 | 8.06 | 500 | 3.2004 | 1.0 | |
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| 3.1004 | 12.1 | 750 | 3.1159 | 1.0 | |
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| 2.3298 | 16.13 | 1000 | 1.0486 | 0.7809 | |
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| 0.5044 | 20.16 | 1250 | 0.6083 | 0.3464 | |
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| 0.27 | 24.19 | 1500 | 0.6948 | 0.2456 | |
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| 0.1833 | 28.23 | 1750 | 0.9908 | 0.1956 | |
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| 0.1324 | 32.26 | 2000 | 1.0134 | 0.1995 | |
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| 0.1027 | 36.29 | 2250 | 1.3176 | 0.1760 | |
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| 0.0852 | 40.32 | 2500 | 1.1929 | 0.1837 | |
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| 0.0703 | 44.35 | 2750 | 1.3824 | 0.1670 | |
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| 0.0601 | 48.39 | 3000 | 1.3337 | 0.1674 | |
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| 0.0546 | 52.42 | 3250 | 1.3566 | 0.1717 | |
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| 0.05 | 56.45 | 3500 | 1.4653 | 0.1670 | |
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| 0.046 | 60.48 | 3750 | 1.4321 | 0.1696 | |
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| 0.0452 | 64.52 | 4000 | 1.4372 | 0.1666 | |
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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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