| | --- |
| | 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: 0.9848965131456274 |
| | --- |
| | |
| | <!-- 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: 0.0374 |
| | - Wer: 0.9849 |
| | - Cer: 0.7098 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
| | | 3.6149 | 1.07 | 400 | 0.4672 | 1.0114 | 0.7588 | |
| | | 0.4341 | 2.15 | 800 | 0.2008 | 0.9972 | 0.7369 | |
| | | 0.2665 | 3.22 | 1200 | 0.1283 | 0.9986 | 0.7180 | |
| | | 0.2114 | 4.3 | 1600 | 0.1016 | 0.9995 | 0.7135 | |
| | | 0.1768 | 5.37 | 2000 | 0.0774 | 0.9950 | 0.7208 | |
| | | 0.1531 | 6.44 | 2400 | 0.0682 | 0.9933 | 0.7137 | |
| | | 0.1352 | 7.52 | 2800 | 0.0690 | 0.9883 | 0.7022 | |
| | | 0.1252 | 8.59 | 3200 | 0.0656 | 0.9925 | 0.7091 | |
| | | 0.1144 | 9.66 | 3600 | 0.0521 | 0.9888 | 0.7124 | |
| | | 0.0986 | 10.74 | 4000 | 0.0527 | 0.9915 | 0.7067 | |
| | | 0.0875 | 11.81 | 4400 | 0.0531 | 0.9902 | 0.7057 | |
| | | 0.0883 | 12.89 | 4800 | 0.0488 | 0.9888 | 0.7136 | |
| | | 0.0812 | 13.96 | 5200 | 0.0461 | 0.9884 | 0.7122 | |
| | | 0.0721 | 15.03 | 5600 | 0.0474 | 0.9884 | 0.7128 | |
| | | 0.0681 | 16.11 | 6000 | 0.0469 | 0.9869 | 0.7243 | |
| | | 0.0671 | 17.18 | 6400 | 0.0450 | 0.9878 | 0.7086 | |
| | | 0.0613 | 18.26 | 6800 | 0.0492 | 0.9852 | 0.7171 | |
| | | 0.0573 | 19.33 | 7200 | 0.0435 | 0.9852 | 0.7209 | |
| | | 0.0531 | 20.4 | 7600 | 0.0389 | 0.9908 | 0.7071 | |
| | | 0.0493 | 21.48 | 8000 | 0.0423 | 0.9871 | 0.7166 | |
| | | 0.0477 | 22.55 | 8400 | 0.0416 | 0.9843 | 0.7127 | |
| | | 0.0441 | 23.62 | 8800 | 0.0372 | 0.9864 | 0.7075 | |
| | | 0.0412 | 24.7 | 9200 | 0.0408 | 0.9857 | 0.7118 | |
| | | 0.0392 | 25.77 | 9600 | 0.0407 | 0.9851 | 0.7152 | |
| | | 0.0359 | 26.85 | 10000 | 0.0383 | 0.9861 | 0.7086 | |
| | | 0.0347 | 27.92 | 10400 | 0.0373 | 0.9852 | 0.7066 | |
| | | 0.0327 | 28.99 | 10800 | 0.0374 | 0.9849 | 0.7098 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.13.3 |
| | |
