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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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- automatic-speech-recognition |
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- librispeech_asr |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-bert-CV16-en-libri |
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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-bert-CV16-en-libri |
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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 LIBRISPEECH_ASR - CLEAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1035 |
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- Wer: 0.0708 |
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- Cer: 0.0194 |
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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: 3e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 72 |
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- total_eval_batch_size: 36 |
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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: 10000 |
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- num_epochs: 7.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:------:|:---------------:|:------:| |
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| 2.8812 | 0.63 | 250 | 1.0000 | 2.8923 | 1.0 | |
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| 1.2899 | 1.26 | 500 | 0.2563 | 1.1471 | 0.7030 | |
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| 0.5276 | 1.89 | 750 | 0.1127 | 0.4687 | 0.4114 | |
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| 0.3313 | 2.52 | 1000 | 0.0659 | 0.2870 | 0.2577 | |
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| 0.2089 | 3.16 | 1250 | 0.0445 | 0.2079 | 0.1766 | |
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| 0.1634 | 3.79 | 1500 | 0.0366 | 0.1687 | 0.1411 | |
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| 0.1546 | 4.42 | 1750 | 0.1452 | 0.1138 | 0.0294 | |
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| 0.1245 | 5.05 | 2000 | 0.1316 | 0.0973 | 0.0260 | |
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| 0.1341 | 5.68 | 2250 | 0.1196 | 0.0867 | 0.0234 | |
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| 0.0942 | 6.31 | 2500 | 0.1128 | 0.0794 | 0.0213 | |
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| 0.0848 | 6.94 | 2750 | 0.1077 | 0.0717 | 0.0197 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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