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--- |
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language: |
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- tr |
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tags: |
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- automatic-speech-recognition |
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- common_voice |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: hello_2b |
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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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# hello_2b |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-2b](https://huggingface.co/facebook/wav2vec2-xls-r-2b) on the COMMON_VOICE - TR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2725 |
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- Wer: 0.9531 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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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: 30.0 |
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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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| 3.1646 | 0.92 | 100 | 3.2106 | 1.0 | |
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| 0.368 | 1.85 | 200 | 2.9963 | 1.0 | |
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| 0.2252 | 2.77 | 300 | 2.8078 | 0.9999 | |
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| 0.1546 | 3.7 | 400 | 2.3458 | 0.9996 | |
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| 0.1468 | 4.63 | 500 | 2.0086 | 0.9986 | |
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| 0.1261 | 5.55 | 600 | 1.8269 | 0.9985 | |
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| 0.1206 | 6.48 | 700 | 1.7347 | 0.9956 | |
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| 0.1959 | 7.4 | 800 | 1.6819 | 0.9955 | |
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| 0.0502 | 8.33 | 900 | 1.6809 | 0.9965 | |
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| 0.0811 | 9.26 | 1000 | 1.6674 | 0.9916 | |
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| 0.0534 | 10.18 | 1100 | 1.5719 | 0.9898 | |
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| 0.0402 | 11.11 | 1200 | 1.4620 | 0.9821 | |
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| 0.057 | 12.04 | 1300 | 1.3015 | 0.9554 | |
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| 0.0385 | 12.96 | 1400 | 1.3798 | 0.9600 | |
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| 0.0422 | 13.88 | 1500 | 1.3538 | 0.9699 | |
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| 0.014 | 14.81 | 1600 | 1.2507 | 0.9443 | |
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| 0.0232 | 15.74 | 1700 | 1.3318 | 0.9465 | |
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| 0.0554 | 16.66 | 1800 | 1.2784 | 0.9462 | |
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| 0.0316 | 17.59 | 1900 | 1.2503 | 0.9481 | |
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| 0.0524 | 18.51 | 2000 | 1.3920 | 0.9604 | |
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| 0.0142 | 19.44 | 2100 | 1.4224 | 0.9698 | |
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| 0.0288 | 20.37 | 2200 | 1.3475 | 0.9635 | |
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| 0.0106 | 21.29 | 2300 | 1.2232 | 0.9264 | |
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| 0.0396 | 22.22 | 2400 | 1.3323 | 0.9615 | |
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| 0.0349 | 23.15 | 2500 | 1.2741 | 0.9587 | |
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| 0.0121 | 24.07 | 2600 | 1.2671 | 0.9586 | |
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| 0.0224 | 24.99 | 2700 | 1.3001 | 0.9611 | |
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| 0.0449 | 25.92 | 2800 | 1.2777 | 0.9572 | |
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| 0.0186 | 26.85 | 2900 | 1.2766 | 0.9607 | |
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| 0.0365 | 27.77 | 3000 | 1.2935 | 0.9598 | |
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| 0.0105 | 28.7 | 3100 | 1.2761 | 0.9588 | |
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| 0.021 | 29.63 | 3200 | 1.2686 | 0.9528 | |
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### Framework versions |
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- Transformers 4.13.0.dev0 |
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- Pytorch 1.10.0 |
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- Datasets 1.15.2.dev0 |
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- Tokenizers 0.10.3 |
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