| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-large-xlsr-53 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - common_voice |
| metrics: |
| - wer |
| model-index: |
| - name: Model_G_2 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: common_voice |
| type: common_voice |
| config: id |
| split: test |
| args: id |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.251258623904531 |
| --- |
| |
| <!-- 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_2 |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3710 |
| - Wer: 0.2513 |
| - Cer: 0.0631 |
| |
| ## 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 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
| | 3.7484 | 3.23 | 400 | 0.5706 | 0.5698 | 0.1477 | |
| | 0.3419 | 6.45 | 800 | 0.4120 | 0.3758 | 0.0924 | |
| | 0.1796 | 9.68 | 1200 | 0.3691 | 0.3295 | 0.0843 | |
| | 0.125 | 12.9 | 1600 | 0.3821 | 0.3097 | 0.0782 | |
| | 0.0984 | 16.13 | 2000 | 0.4085 | 0.2947 | 0.0742 | |
| | 0.0827 | 19.35 | 2400 | 0.3859 | 0.2781 | 0.0711 | |
| | 0.0666 | 22.58 | 2800 | 0.3813 | 0.2663 | 0.0684 | |
| | 0.0558 | 25.81 | 3200 | 0.3681 | 0.2545 | 0.0644 | |
| | 0.0466 | 29.03 | 3600 | 0.3710 | 0.2513 | 0.0631 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 1.18.3 |
| - Tokenizers 0.13.3 |
| |
