| | --- |
| | license: apache-2.0 |
| | base_model: facebook/wav2vec2-large-xlsr-53 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - common_voice_7_0 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: luganda_wav2vec2_ctc_train_clean |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: common_voice_7_0 |
| | type: common_voice_7_0 |
| | config: lg |
| | split: None |
| | args: lg |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 0.4156354350815164 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # luganda_wav2vec2_ctc_train_clean |
| |
|
| | 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_7_0 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2835 |
| | - Wer: 0.4156 |
| | |
| | ## 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: 0.0001 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 1000 |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 5.8861 | 2.4 | 500 | 3.1284 | 1.0 | |
| | | 2.0448 | 4.81 | 1000 | 0.5439 | 0.7131 | |
| | | 0.6342 | 7.21 | 1500 | 0.3713 | 0.5556 | |
| | | 0.4907 | 9.62 | 2000 | 0.3464 | 0.5015 | |
| | | 0.4242 | 12.02 | 2500 | 0.3122 | 0.4746 | |
| | | 0.3898 | 14.42 | 3000 | 0.3164 | 0.4634 | |
| | | 0.357 | 16.83 | 3500 | 0.2896 | 0.4416 | |
| | | 0.3338 | 19.23 | 4000 | 0.2880 | 0.4409 | |
| | | 0.3223 | 21.63 | 4500 | 0.2841 | 0.4287 | |
| | | 0.3072 | 24.04 | 5000 | 0.2849 | 0.4250 | |
| | | 0.2974 | 26.44 | 5500 | 0.2829 | 0.4194 | |
| | | 0.2878 | 28.85 | 6000 | 0.2835 | 0.4156 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.1 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.17.0 |
| | - Tokenizers 0.15.2 |
| |
|
