| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | base_model: facebook/wav2vec2-base |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: output_model |
| | 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. --> |
| |
|
| | # output_model |
| | |
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2884 |
| | - Wer: 0.4752 |
| | |
| | ## 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: 8 |
| | - 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 | |
| | |:-------------:|:-------:|:----:|:---------------:|:------:| |
| | | 2.8783 | 2.4752 | 500 | 2.7618 | 0.9999 | |
| | | 1.4069 | 4.9505 | 1000 | 1.0853 | 0.6936 | |
| | | 0.6264 | 7.4257 | 1500 | 0.9955 | 0.6014 | |
| | | 0.3864 | 9.9010 | 2000 | 1.0460 | 0.5675 | |
| | | 0.2714 | 12.3762 | 2500 | 0.9830 | 0.5422 | |
| | | 0.2099 | 14.8515 | 3000 | 1.0333 | 0.5296 | |
| | | 0.1615 | 17.3267 | 3500 | 1.1575 | 0.5203 | |
| | | 0.1248 | 19.8020 | 4000 | 1.1311 | 0.4956 | |
| | | 0.1032 | 22.2772 | 4500 | 1.3206 | 0.4953 | |
| | | 0.0834 | 24.7525 | 5000 | 1.2094 | 0.4855 | |
| | | 0.0655 | 27.2277 | 5500 | 1.2966 | 0.4763 | |
| | | 0.052 | 29.7030 | 6000 | 1.2884 | 0.4752 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.40.0 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| |
|
