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--- |
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license: mit |
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base_model: facebook/w2v-bert-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_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-test_arm-colab-CV16.0 |
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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: hy-AM |
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split: test |
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args: hy-AM |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.1774802773129333 |
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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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# w2v-bert-2.0-test_arm-colab-CV16.0 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) 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: 0.2066 |
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- Wer: 0.1775 |
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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: 5e-05 |
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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: 10 |
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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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| 0.1471 | 1.6 | 300 | 0.2062 | 0.2229 | |
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| 0.1437 | 3.2 | 600 | 0.2216 | 0.2375 | |
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| 0.1051 | 4.8 | 900 | 0.1969 | 0.2127 | |
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| 0.0594 | 6.4 | 1200 | 0.1882 | 0.1839 | |
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| 0.0297 | 8.0 | 1500 | 0.1951 | 0.1825 | |
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| 0.0115 | 9.6 | 1800 | 0.2066 | 0.1775 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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