| | --- |
| | license: apache-2.0 |
| | base_model: facebook/wav2vec2-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - common_voice_1_0 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: finetuning2 |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: common_voice_1_0 |
| | type: common_voice_1_0 |
| | config: en |
| | split: validation |
| | args: en |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 0.4213759213759214 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # finetuning2 |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_1_0 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6883 |
| | - Wer: 0.4214 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 4.5277 | 4.27 | 500 | 2.8353 | 0.9863 | |
| | | 1.2768 | 8.55 | 1000 | 0.7019 | 0.5581 | |
| | | 0.4511 | 12.82 | 1500 | 0.6201 | 0.4726 | |
| | | 0.2591 | 17.09 | 2000 | 0.6428 | 0.4469 | |
| | | 0.1854 | 21.37 | 2500 | 0.6901 | 0.4388 | |
| | | 0.1386 | 25.64 | 3000 | 0.6933 | 0.4259 | |
| | | 0.111 | 29.91 | 3500 | 0.6883 | 0.4214 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.39.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| |
|
