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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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metrics: |
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- wer |
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model-index: |
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- name: Check_Model_2 |
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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: common_voice |
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type: common_voice |
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config: id |
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split: test |
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args: id |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.2728883087823979 |
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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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# Check_Model_2 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3499 |
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- Wer: 0.2729 |
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- Cer: 0.0673 |
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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: 16 |
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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: 32 |
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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 |
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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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| 3.8708 | 3.23 | 400 | 0.7345 | 0.7259 | 0.2034 | |
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| 0.4247 | 6.45 | 800 | 0.4128 | 0.4268 | 0.1102 | |
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| 0.2047 | 9.68 | 1200 | 0.3726 | 0.3795 | 0.0930 | |
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| 0.1422 | 12.9 | 1600 | 0.3690 | 0.3514 | 0.0884 | |
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| 0.1139 | 16.13 | 2000 | 0.3811 | 0.3160 | 0.0794 | |
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| 0.089 | 19.35 | 2400 | 0.3650 | 0.2895 | 0.0731 | |
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| 0.0709 | 22.58 | 2800 | 0.3629 | 0.2944 | 0.0727 | |
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| 0.0594 | 25.81 | 3200 | 0.3538 | 0.2779 | 0.0692 | |
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| 0.0478 | 29.03 | 3600 | 0.3499 | 0.2729 | 0.0673 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.3 |
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