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--- |
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language: |
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- he |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- robust-speech-event |
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- he |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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base_model: facebook/wav2vec2-xls-r-1b |
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model-index: |
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- name: wav2vec2-xls-r-1b-hebrew |
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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-xls-r-1b-hebrew |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3533 |
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- Wer: 0.2251 |
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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: 6 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 24 |
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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: 400 |
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- num_epochs: 20.0 |
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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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| 3.3587 | 0.47 | 400 | 1.1883 | 0.8392 | |
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| 1.8377 | 0.95 | 800 | 0.8831 | 0.6852 | |
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| 1.7118 | 1.42 | 1200 | 0.8031 | 0.6566 | |
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| 1.6741 | 1.89 | 1600 | 0.7518 | 0.6104 | |
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| 1.6163 | 2.36 | 2000 | 0.6888 | 0.5591 | |
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| 1.5782 | 2.84 | 2400 | 0.6580 | 0.5165 | |
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| 1.5548 | 3.31 | 2800 | 0.6506 | 0.5184 | |
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| 1.5249 | 3.78 | 3200 | 0.6198 | 0.5028 | |
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| 1.5078 | 4.26 | 3600 | 0.5992 | 0.4932 | |
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| 1.4836 | 4.73 | 4000 | 0.5705 | 0.4651 | |
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| 1.4505 | 5.2 | 4400 | 0.5489 | 0.4508 | |
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| 1.4481 | 5.67 | 4800 | 0.5577 | 0.4562 | |
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| 1.4136 | 6.15 | 5200 | 0.5452 | 0.4371 | |
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| 1.3861 | 6.62 | 5600 | 0.5101 | 0.4087 | |
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| 1.3772 | 7.09 | 6000 | 0.4933 | 0.3951 | |
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| 1.3478 | 7.56 | 6400 | 0.4849 | 0.3922 | |
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| 1.3394 | 8.04 | 6800 | 0.4805 | 0.3892 | |
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| 1.3095 | 8.51 | 7200 | 0.4839 | 0.3834 | |
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| 1.306 | 8.98 | 7600 | 0.4611 | 0.3587 | |
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| 1.2707 | 9.46 | 8000 | 0.4545 | 0.3730 | |
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| 1.2626 | 9.93 | 8400 | 0.4516 | 0.3524 | |
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| 1.2412 | 10.4 | 8800 | 0.4314 | 0.3310 | |
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| 1.2456 | 10.87 | 9200 | 0.4401 | 0.3459 | |
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| 1.2081 | 11.35 | 9600 | 0.4399 | 0.3356 | |
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| 1.1998 | 11.82 | 10000 | 0.4195 | 0.3215 | |
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| 1.1826 | 12.29 | 10400 | 0.4221 | 0.3178 | |
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| 1.1573 | 12.77 | 10800 | 0.4098 | 0.3084 | |
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| 1.1416 | 13.24 | 11200 | 0.4086 | 0.3119 | |
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| 1.1174 | 13.71 | 11600 | 0.3854 | 0.2910 | |
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| 1.1048 | 14.18 | 12000 | 0.3859 | 0.2824 | |
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| 1.0748 | 14.66 | 12400 | 0.3854 | 0.2757 | |
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| 1.0697 | 15.13 | 12800 | 0.3740 | 0.2724 | |
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| 1.0477 | 15.6 | 13200 | 0.3693 | 0.2643 | |
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| 1.0356 | 16.08 | 13600 | 0.3727 | 0.2561 | |
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| 1.0083 | 16.55 | 14000 | 0.3652 | 0.2501 | |
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| 1.0 | 17.02 | 14400 | 0.3641 | 0.2457 | |
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| 0.9779 | 17.49 | 14800 | 0.3568 | 0.2409 | |
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| 0.9596 | 17.97 | 15200 | 0.3558 | 0.2376 | |
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| 0.946 | 18.44 | 15600 | 0.3591 | 0.2311 | |
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| 0.9389 | 18.91 | 16000 | 0.3540 | 0.2283 | |
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| 0.9173 | 19.39 | 16400 | 0.3552 | 0.2265 | |
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| 0.9122 | 19.86 | 16800 | 0.3535 | 0.2250 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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