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--- |
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library_name: transformers |
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language: |
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- lg |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Grain |
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metrics: |
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- wer |
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model-index: |
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- name: w |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Grain |
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type: Grain |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.029878515924263983 |
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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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# w |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co./facebook/w2v-bert-2.0) on the Grain dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0469 |
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- Wer: 0.0299 |
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- Cer: 0.0077 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 0.2995 | 1.0 | 1164 | 0.1521 | 0.1390 | 0.0283 | |
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| 0.1049 | 2.0 | 2328 | 0.0931 | 0.0946 | 0.0189 | |
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| 0.0719 | 3.0 | 3492 | 0.0861 | 0.0902 | 0.0183 | |
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| 0.0546 | 4.0 | 4656 | 0.0788 | 0.0704 | 0.0166 | |
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| 0.0447 | 5.0 | 5820 | 0.0609 | 0.0627 | 0.0135 | |
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| 0.0374 | 6.0 | 6984 | 0.0744 | 0.0618 | 0.0141 | |
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| 0.0338 | 7.0 | 8148 | 0.0673 | 0.0535 | 0.0137 | |
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| 0.029 | 8.0 | 9312 | 0.0770 | 0.0540 | 0.0128 | |
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| 0.0278 | 9.0 | 10476 | 0.0565 | 0.0482 | 0.0116 | |
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| 0.0227 | 10.0 | 11640 | 0.0516 | 0.0500 | 0.0115 | |
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| 0.0211 | 11.0 | 12804 | 0.0457 | 0.0392 | 0.0096 | |
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| 0.0207 | 12.0 | 13968 | 0.0527 | 0.0452 | 0.0098 | |
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| 0.0179 | 13.0 | 15132 | 0.0463 | 0.0370 | 0.0089 | |
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| 0.017 | 14.0 | 16296 | 0.0530 | 0.0452 | 0.0109 | |
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| 0.0167 | 15.0 | 17460 | 0.0447 | 0.0360 | 0.0091 | |
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| 0.0141 | 16.0 | 18624 | 0.0529 | 0.0434 | 0.0104 | |
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| 0.015 | 17.0 | 19788 | 0.0410 | 0.0387 | 0.0090 | |
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| 0.0141 | 18.0 | 20952 | 0.0480 | 0.0416 | 0.0102 | |
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| 0.0136 | 19.0 | 22116 | 0.0472 | 0.0368 | 0.0087 | |
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| 0.0125 | 20.0 | 23280 | 0.0428 | 0.0380 | 0.0091 | |
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| 0.0117 | 21.0 | 24444 | 0.0375 | 0.0328 | 0.0081 | |
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| 0.0113 | 22.0 | 25608 | 0.0392 | 0.0312 | 0.0083 | |
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| 0.0093 | 23.0 | 26772 | 0.0554 | 0.0394 | 0.0102 | |
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| 0.0111 | 24.0 | 27936 | 0.0624 | 0.0452 | 0.0108 | |
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| 0.0107 | 25.0 | 29100 | 0.0390 | 0.0346 | 0.0076 | |
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| 0.0082 | 26.0 | 30264 | 0.0505 | 0.0426 | 0.0101 | |
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| 0.0087 | 27.0 | 31428 | 0.0430 | 0.0320 | 0.0081 | |
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| 0.0086 | 28.0 | 32592 | 0.0541 | 0.0398 | 0.0101 | |
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| 0.0079 | 29.0 | 33756 | 0.0404 | 0.0304 | 0.0070 | |
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| 0.0084 | 30.0 | 34920 | 0.0416 | 0.0315 | 0.0075 | |
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| 0.0084 | 31.0 | 36084 | 0.0495 | 0.0366 | 0.0092 | |
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| 0.0075 | 32.0 | 37248 | 0.0469 | 0.0299 | 0.0077 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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