| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - common_voice |
| | model-index: |
| | - name: Model_G_Wav2Vec2_Versi1 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # Model_G_Wav2Vec2_Versi1 |
| | |
| | This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4072 |
| | - Wer: 1.0101 |
| | - Cer: 0.7622 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0003 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
| | | 3.7506 | 5.97 | 400 | 0.6970 | 1.0124 | 0.7636 | |
| | | 0.3678 | 11.94 | 800 | 0.4711 | 1.0290 | 0.7660 | |
| | | 0.1612 | 17.91 | 1200 | 0.4492 | 1.0007 | 0.7606 | |
| | | 0.1056 | 23.88 | 1600 | 0.4012 | 1.0040 | 0.7658 | |
| | | 0.0693 | 29.85 | 2000 | 0.4072 | 1.0101 | 0.7622 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.11.3 |
| | - Pytorch 1.10.0+cu113 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.10.3 |
| |
|
