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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_1 |
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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-amharic-demo-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_1 |
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type: common_voice_16_1 |
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config: am |
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split: test |
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args: am |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.8639092728485657 |
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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-amharic-demo-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_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6333 |
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- Wer: 0.8639 |
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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: 100 |
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- num_epochs: 60 |
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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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| 12.6948 | 5.0 | 100 | 4.1621 | 1.0 | |
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| 4.1026 | 10.0 | 200 | 4.0365 | 1.0 | |
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| 4.0037 | 15.0 | 300 | 3.9726 | 1.0007 | |
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| 3.9485 | 20.0 | 400 | 3.9524 | 1.0007 | |
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| 3.4635 | 25.0 | 500 | 2.4384 | 0.9980 | |
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| 1.1709 | 30.0 | 600 | 1.6987 | 0.9453 | |
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| 0.4955 | 35.0 | 700 | 1.5927 | 0.9073 | |
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| 0.3163 | 40.0 | 800 | 1.6750 | 0.8833 | |
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| 0.2372 | 45.0 | 900 | 1.6683 | 0.8813 | |
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| 0.1896 | 50.0 | 1000 | 1.6555 | 0.8779 | |
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| 0.1619 | 55.0 | 1100 | 1.6312 | 0.8819 | |
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| 0.1473 | 60.0 | 1200 | 1.6333 | 0.8639 | |
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### Framework versions |
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- Transformers 4.42.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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