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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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datasets: |
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- fleurs |
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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-filtered-100hrs-v12 |
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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: fleurs |
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type: fleurs |
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config: lg_ug |
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split: test |
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args: lg_ug |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.43848396501457726 |
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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-filtered-100hrs-v12 |
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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 fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4980 |
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- Wer: 0.4385 |
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- Cer: 0.0852 |
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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: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 70 |
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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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| 0.9834 | 1.0 | 7125 | 0.3827 | 0.4584 | 0.0921 | |
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| 0.1914 | 2.0 | 14250 | 0.3460 | 0.4394 | 0.0837 | |
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| 0.165 | 3.0 | 21375 | 0.3377 | 0.4375 | 0.0827 | |
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| 0.1519 | 4.0 | 28500 | 0.3337 | 0.4246 | 0.0805 | |
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| 0.1458 | 5.0 | 35625 | 0.3242 | 0.4234 | 0.0789 | |
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| 0.1413 | 6.0 | 42750 | 0.3294 | 0.4329 | 0.0816 | |
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| 0.1395 | 7.0 | 49875 | 0.3441 | 0.4431 | 0.0866 | |
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| 0.1325 | 8.0 | 57000 | 0.3263 | 0.4332 | 0.0867 | |
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| 0.1191 | 9.0 | 64125 | 0.3278 | 0.4065 | 0.0788 | |
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| 0.1075 | 10.0 | 71250 | 0.3203 | 0.4418 | 0.0808 | |
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| 0.0974 | 11.0 | 78375 | 0.3304 | 0.4036 | 0.0771 | |
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| 0.0892 | 12.0 | 85500 | 0.3307 | 0.4263 | 0.0819 | |
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| 0.0802 | 13.0 | 92625 | 0.3530 | 0.4107 | 0.0785 | |
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| 0.0728 | 14.0 | 99750 | 0.3478 | 0.4156 | 0.0795 | |
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| 0.0632 | 15.0 | 106875 | 0.3620 | 0.4052 | 0.0787 | |
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| 0.0567 | 16.0 | 114000 | 0.3620 | 0.4219 | 0.0796 | |
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| 0.0484 | 17.0 | 121125 | 0.4135 | 0.4114 | 0.0787 | |
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| 0.0423 | 18.0 | 128250 | 0.4220 | 0.4186 | 0.0814 | |
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| 0.0358 | 19.0 | 135375 | 0.4476 | 0.4303 | 0.0825 | |
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| 0.0311 | 20.0 | 142500 | 0.4913 | 0.4134 | 0.0806 | |
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| 0.0277 | 21.0 | 149625 | 0.4910 | 0.4411 | 0.0850 | |
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| 0.0238 | 22.0 | 156750 | 0.5097 | 0.4269 | 0.0821 | |
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| 0.0214 | 23.0 | 163875 | 0.4755 | 0.4248 | 0.0837 | |
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| 0.0194 | 24.0 | 171000 | 0.4839 | 0.4249 | 0.0826 | |
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| 0.0178 | 25.0 | 178125 | 0.5302 | 0.4294 | 0.0828 | |
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| 0.016 | 26.0 | 185250 | 0.4980 | 0.4385 | 0.0852 | |
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### Framework versions |
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- Transformers 4.46.2 |
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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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