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--- |
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library_name: transformers |
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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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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-lg-CV-Fleurs-5hrs-v10 |
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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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# w2v-bert-2.0-lg-CV-Fleurs-5hrs-v10 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8414 |
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- Wer: 0.3891 |
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- Cer: 0.0838 |
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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: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 1.6631 | 1.0 | 163 | 0.5729 | 0.5671 | 0.1312 | |
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| 0.4064 | 2.0 | 326 | 0.4681 | 0.4766 | 0.1051 | |
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| 0.3071 | 3.0 | 489 | 0.4348 | 0.4344 | 0.0961 | |
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| 0.2518 | 4.0 | 652 | 0.4442 | 0.4112 | 0.0885 | |
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| 0.2154 | 5.0 | 815 | 0.4503 | 0.4042 | 0.0877 | |
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| 0.1824 | 6.0 | 978 | 0.4146 | 0.4287 | 0.0910 | |
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| 0.1625 | 7.0 | 1141 | 0.4245 | 0.4082 | 0.0878 | |
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| 0.1354 | 8.0 | 1304 | 0.4579 | 0.4335 | 0.0881 | |
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| 0.1182 | 9.0 | 1467 | 0.4593 | 0.4242 | 0.0916 | |
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| 0.1025 | 10.0 | 1630 | 0.4587 | 0.4046 | 0.0881 | |
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| 0.0863 | 11.0 | 1793 | 0.5591 | 0.3991 | 0.0854 | |
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| 0.0723 | 12.0 | 1956 | 0.4954 | 0.4041 | 0.0863 | |
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| 0.0619 | 13.0 | 2119 | 0.5618 | 0.4127 | 0.0890 | |
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| 0.0543 | 14.0 | 2282 | 0.5675 | 0.4115 | 0.0892 | |
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| 0.0461 | 15.0 | 2445 | 0.6027 | 0.3968 | 0.0861 | |
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| 0.0412 | 16.0 | 2608 | 0.5939 | 0.4138 | 0.0895 | |
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| 0.0348 | 17.0 | 2771 | 0.6687 | 0.4157 | 0.0894 | |
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| 0.0342 | 18.0 | 2934 | 0.7066 | 0.3849 | 0.0838 | |
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| 0.0288 | 19.0 | 3097 | 0.7669 | 0.3899 | 0.0849 | |
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| 0.0233 | 20.0 | 3260 | 0.6945 | 0.4000 | 0.0865 | |
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| 0.0218 | 21.0 | 3423 | 0.7192 | 0.4086 | 0.0883 | |
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| 0.02 | 22.0 | 3586 | 0.6980 | 0.3940 | 0.0843 | |
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| 0.017 | 23.0 | 3749 | 0.7983 | 0.4014 | 0.0873 | |
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| 0.0153 | 24.0 | 3912 | 0.7599 | 0.3942 | 0.0853 | |
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| 0.0142 | 25.0 | 4075 | 0.7761 | 0.3993 | 0.0858 | |
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| 0.0137 | 26.0 | 4238 | 0.7491 | 0.3996 | 0.0857 | |
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| 0.0157 | 27.0 | 4401 | 0.7682 | 0.3994 | 0.0858 | |
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| 0.0113 | 28.0 | 4564 | 0.7784 | 0.4006 | 0.0875 | |
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| 0.0111 | 29.0 | 4727 | 0.8020 | 0.4020 | 0.0864 | |
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| 0.0105 | 30.0 | 4890 | 0.8414 | 0.3891 | 0.0838 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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