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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_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-hi-colab |
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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_16_0 |
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type: common_voice_16_0 |
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config: hi |
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split: test |
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args: hi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.4948465637275874 |
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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-large-xls-r-300m-hi-colab |
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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_16_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6983 |
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- Wer: 0.4948 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 5.491 | 1.8059 | 400 | 1.3703 | 0.9679 | |
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| 0.6981 | 3.6117 | 800 | 0.7041 | 0.6607 | |
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| 0.3758 | 5.4176 | 1200 | 0.6709 | 0.6185 | |
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| 0.2736 | 7.2235 | 1600 | 0.7170 | 0.5925 | |
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| 0.2089 | 9.0293 | 2000 | 0.6445 | 0.5722 | |
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| 0.1686 | 10.8352 | 2400 | 0.7004 | 0.5770 | |
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| 0.1408 | 12.6411 | 2800 | 0.7097 | 0.5735 | |
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| 0.1227 | 14.4470 | 3200 | 0.6763 | 0.5533 | |
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| 0.1056 | 16.2528 | 3600 | 0.7245 | 0.5484 | |
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| 0.0923 | 18.0587 | 4000 | 0.7198 | 0.5480 | |
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| 0.083 | 19.8646 | 4400 | 0.6568 | 0.5251 | |
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| 0.0742 | 21.6704 | 4800 | 0.7183 | 0.5252 | |
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| 0.0647 | 23.4763 | 5200 | 0.7306 | 0.5141 | |
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| 0.0574 | 25.2822 | 5600 | 0.7236 | 0.5063 | |
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| 0.052 | 27.0880 | 6000 | 0.7234 | 0.4969 | |
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| 0.0478 | 28.8939 | 6400 | 0.6983 | 0.4948 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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