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--- |
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license: apache-2.0 |
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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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model-index: |
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- name: wav2vec2-large-xls-r-300m-hsb-v3 |
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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-large-xls-r-300m-hsb-v3 |
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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: 0.6549 |
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- Wer: 0.4827 |
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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: 0.00045 |
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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: 50 |
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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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| 8.8951 | 3.23 | 100 | 3.6396 | 1.0 | |
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| 3.314 | 6.45 | 200 | 3.2331 | 1.0 | |
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| 3.1931 | 9.68 | 300 | 3.0947 | 0.9906 | |
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| 1.7079 | 12.9 | 400 | 0.8865 | 0.8499 | |
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| 0.6859 | 16.13 | 500 | 0.7994 | 0.7529 | |
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| 0.4804 | 19.35 | 600 | 0.7783 | 0.7069 | |
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| 0.3506 | 22.58 | 700 | 0.6904 | 0.6321 | |
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| 0.2695 | 25.81 | 800 | 0.6519 | 0.5926 | |
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| 0.222 | 29.03 | 900 | 0.7041 | 0.5720 | |
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| 0.1828 | 32.26 | 1000 | 0.6608 | 0.5513 | |
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| 0.1474 | 35.48 | 1100 | 0.7129 | 0.5319 | |
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| 0.1269 | 38.71 | 1200 | 0.6664 | 0.5056 | |
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| 0.1077 | 41.94 | 1300 | 0.6712 | 0.4942 | |
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| 0.0934 | 45.16 | 1400 | 0.6467 | 0.4879 | |
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| 0.0819 | 48.39 | 1500 | 0.6549 | 0.4827 | |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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