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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- automatic-speech-recognition |
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- ./sample_speech.py |
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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: en-xlsr |
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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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# en-xlsr |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5356 |
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- Cer: 0.0853 |
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- Wer: 0.1884 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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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_ratio: 0.01 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 0.7055 | 2.79 | 600 | 0.4911 | 0.1304 | 0.3308 | |
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| 0.3761 | 5.58 | 1200 | 0.3984 | 0.1053 | 0.2533 | |
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| 0.278 | 8.37 | 1800 | 0.4070 | 0.1024 | 0.2445 | |
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| 0.2196 | 11.16 | 2400 | 0.4033 | 0.0974 | 0.2243 | |
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| 0.1842 | 13.95 | 3000 | 0.4270 | 0.0928 | 0.2106 | |
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| 0.1533 | 16.74 | 3600 | 0.4582 | 0.0916 | 0.2071 | |
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| 0.1257 | 19.53 | 4200 | 0.4685 | 0.0901 | 0.2001 | |
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| 0.1071 | 22.33 | 4800 | 0.5088 | 0.0878 | 0.1965 | |
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| 0.0967 | 25.12 | 5400 | 0.5224 | 0.0872 | 0.1913 | |
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| 0.0839 | 27.91 | 6000 | 0.5379 | 0.0860 | 0.1885 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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