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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: wav2vec2-large-xlsr-53_train_data_full |
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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_train_data_full |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4168 |
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- Wer: 0.3383 |
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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: 16 |
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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: 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: 1000 |
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- num_epochs: 20 |
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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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| 3.0459 | 0.73 | 500 | 3.2037 | 0.9995 | |
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| 0.7938 | 1.45 | 1000 | 0.7432 | 0.6373 | |
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| 0.503 | 2.18 | 1500 | 0.5517 | 0.5115 | |
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| 0.4475 | 2.91 | 2000 | 0.4916 | 0.4624 | |
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| 0.3575 | 3.63 | 2500 | 0.4612 | 0.4362 | |
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| 0.3206 | 4.36 | 3000 | 0.4546 | 0.4198 | |
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| 0.3155 | 5.09 | 3500 | 0.4073 | 0.3929 | |
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| 0.2827 | 5.81 | 4000 | 0.4172 | 0.3808 | |
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| 0.2575 | 6.54 | 4500 | 0.4183 | 0.3741 | |
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| 0.2399 | 7.27 | 5000 | 0.4181 | 0.3680 | |
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| 0.2455 | 7.99 | 5500 | 0.3981 | 0.3604 | |
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| 0.2512 | 8.72 | 6000 | 0.4203 | 0.3612 | |
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| 0.221 | 9.45 | 6500 | 0.4073 | 0.3560 | |
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| 0.19 | 10.17 | 7000 | 0.4206 | 0.3547 | |
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| 0.207 | 10.9 | 7500 | 0.3992 | 0.3517 | |
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| 0.187 | 11.63 | 8000 | 0.4078 | 0.3517 | |
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| 0.2029 | 12.35 | 8500 | 0.4143 | 0.3469 | |
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| 0.171 | 13.08 | 9000 | 0.4007 | 0.3430 | |
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| 0.1658 | 13.81 | 9500 | 0.3862 | 0.3422 | |
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| 0.2021 | 14.53 | 10000 | 0.4132 | 0.3454 | |
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| 0.165 | 15.26 | 10500 | 0.3997 | 0.3407 | |
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| 0.1562 | 15.99 | 11000 | 0.4069 | 0.3416 | |
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| 0.1613 | 16.71 | 11500 | 0.4040 | 0.3393 | |
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| 0.1713 | 17.44 | 12000 | 0.4094 | 0.3411 | |
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| 0.1541 | 18.17 | 12500 | 0.4043 | 0.3367 | |
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| 0.144 | 18.89 | 13000 | 0.4086 | 0.3374 | |
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| 0.1483 | 19.62 | 13500 | 0.4168 | 0.3383 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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