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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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model-index: |
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- name: jako-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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# jako-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: 0.9486 |
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- Cer: 0.2606 |
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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: 2 |
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- total_train_batch_size: 32 |
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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: 0.03 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 3.5667 | 1.14 | 1000 | 2.2323 | 0.5188 | |
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| 1.5569 | 2.28 | 2000 | 1.3106 | 0.3527 | |
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| 1.2238 | 3.43 | 3000 | 1.1109 | 0.3099 | |
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| 1.0593 | 4.57 | 4000 | 1.0390 | 0.2891 | |
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| 0.9658 | 5.71 | 5000 | 0.9731 | 0.2918 | |
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| 0.8796 | 6.85 | 6000 | 0.9479 | 0.2696 | |
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| 0.8022 | 8.0 | 7000 | 0.9331 | 0.2710 | |
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| 0.7392 | 9.14 | 8000 | 0.9252 | 0.2746 | |
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| 0.6694 | 10.28 | 9000 | 0.9318 | 0.2590 | |
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| 0.5977 | 11.42 | 10000 | 0.9349 | 0.2674 | |
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| 0.5484 | 12.56 | 11000 | 0.9409 | 0.2555 | |
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| 0.5154 | 13.71 | 12000 | 0.9510 | 0.2719 | |
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| 0.4767 | 14.85 | 13000 | 0.9556 | 0.2624 | |
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| 0.4536 | 15.99 | 14000 | 0.9850 | 0.2684 | |
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| 0.4195 | 17.13 | 15000 | 0.9894 | 0.2590 | |
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| 0.3937 | 18.28 | 16000 | 1.0197 | 0.2698 | |
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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 2.14.6 |
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- Tokenizers 0.14.1 |
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