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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_17_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-sv |
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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_17_0 |
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type: common_voice_17_0 |
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config: sv-SE |
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split: test |
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args: sv-SE |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.10046931592103249 |
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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-sv |
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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_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1962 |
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- Wer: 0.1005 |
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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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| 2.075 | 0.7407 | 300 | 0.3441 | 0.3057 | |
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| 0.2837 | 1.4815 | 600 | 0.2995 | 0.2274 | |
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| 0.2081 | 2.2222 | 900 | 0.2443 | 0.1768 | |
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| 0.1579 | 2.9630 | 1200 | 0.2143 | 0.1493 | |
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| 0.1248 | 3.7037 | 1500 | 0.2165 | 0.1504 | |
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| 0.0934 | 4.4444 | 1800 | 0.1869 | 0.1284 | |
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| 0.0719 | 5.1852 | 2100 | 0.2072 | 0.1216 | |
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| 0.0573 | 5.9259 | 2400 | 0.1949 | 0.1195 | |
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| 0.0436 | 6.6667 | 2700 | 0.2025 | 0.1142 | |
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| 0.0317 | 7.4074 | 3000 | 0.2003 | 0.1097 | |
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| 0.0256 | 8.1481 | 3300 | 0.1942 | 0.1060 | |
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| 0.0169 | 8.8889 | 3600 | 0.1851 | 0.1030 | |
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| 0.0121 | 9.6296 | 3900 | 0.1962 | 0.1005 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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