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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-1b |
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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: wav2vec2-xslr-tr-testv2 |
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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-xslr-tr-testv2 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2789 |
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- Wer: 0.4783 |
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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: 0.0003 |
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- train_batch_size: 4 |
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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: 8 |
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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: 500 |
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- num_epochs: 5.0 |
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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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| No log | 0.1375 | 100 | 2.9646 | 1.0 | |
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| No log | 0.2749 | 200 | 0.9689 | 0.9848 | |
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| No log | 0.4124 | 300 | 0.8561 | 0.9170 | |
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| No log | 0.5498 | 400 | 0.7970 | 0.912 | |
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| 1.9898 | 0.6873 | 500 | 0.8464 | 0.9258 | |
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| 1.9898 | 0.8247 | 600 | 0.7358 | 0.8872 | |
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| 1.9898 | 0.9622 | 700 | 0.6374 | 0.8608 | |
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| 1.9898 | 1.0997 | 800 | 0.5180 | 0.7297 | |
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| 1.9898 | 1.2371 | 900 | 0.4852 | 0.7212 | |
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| 0.663 | 1.3746 | 1000 | 0.4840 | 0.7278 | |
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| 0.663 | 1.5120 | 1100 | 0.4626 | 0.7135 | |
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| 0.663 | 1.6495 | 1200 | 0.4493 | 0.676 | |
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| 0.663 | 1.7869 | 1300 | 0.4419 | 0.6813 | |
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| 0.663 | 1.9244 | 1400 | 0.4306 | 0.6749 | |
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| 0.5455 | 2.0619 | 1500 | 0.4329 | 0.6846 | |
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| 0.5455 | 2.1993 | 1600 | 0.4227 | 0.6685 | |
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| 0.5455 | 2.3368 | 1700 | 0.4097 | 0.6472 | |
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| 0.5455 | 2.4742 | 1800 | 0.4035 | 0.6343 | |
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| 0.5455 | 2.6117 | 1900 | 0.4041 | 0.6304 | |
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| 0.433 | 2.7491 | 2000 | 0.3962 | 0.6542 | |
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| 0.433 | 2.8866 | 2100 | 0.3601 | 0.6041 | |
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| 0.433 | 3.0241 | 2200 | 0.3473 | 0.5864 | |
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| 0.433 | 3.1615 | 2300 | 0.3456 | 0.5723 | |
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| 0.433 | 3.2990 | 2400 | 0.3380 | 0.5617 | |
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| 0.3509 | 3.4364 | 2500 | 0.3267 | 0.5563 | |
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| 0.3509 | 3.5739 | 2600 | 0.3208 | 0.5570 | |
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| 0.3509 | 3.7113 | 2700 | 0.3124 | 0.5397 | |
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| 0.3509 | 3.8488 | 2800 | 0.3038 | 0.5272 | |
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| 0.3509 | 3.9863 | 2900 | 0.2994 | 0.5254 | |
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| 0.2871 | 4.1237 | 3000 | 0.3073 | 0.5247 | |
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| 0.2871 | 4.2612 | 3100 | 0.3009 | 0.5122 | |
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| 0.2871 | 4.3986 | 3200 | 0.2975 | 0.4953 | |
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| 0.2871 | 4.5361 | 3300 | 0.2898 | 0.4938 | |
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| 0.2871 | 4.6735 | 3400 | 0.2835 | 0.4902 | |
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| 0.2198 | 4.8110 | 3500 | 0.2804 | 0.4802 | |
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| 0.2198 | 4.9485 | 3600 | 0.2789 | 0.4783 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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