| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-xls-r-300m |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: 1-epochs5-char-based-freeze_cnn-dropout0.1 |
| 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. --> |
|
|
| # 1-epochs5-char-based-freeze_cnn-dropout0.1 |
| |
| This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1245 |
| - Wer: 0.0865 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 10 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - total_train_batch_size: 40 |
| - total_eval_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:| |
| | 2.8545 | 0.37 | 2500 | 2.8872 | 1.0 | |
| | 0.7012 | 0.74 | 5000 | 0.3473 | 0.2840 | |
| | 0.46 | 1.11 | 7500 | 0.2032 | 0.1510 | |
| | 0.3848 | 1.48 | 10000 | 0.1668 | 0.1194 | |
| | 0.3535 | 1.85 | 12500 | 0.1518 | 0.1086 | |
| | 0.3667 | 2.22 | 15000 | 0.1442 | 0.1019 | |
| | 0.3058 | 2.59 | 17500 | 0.1381 | 0.0961 | |
| | 0.3026 | 2.96 | 20000 | 0.1327 | 0.0924 | |
| | 0.2891 | 3.33 | 22500 | 0.1326 | 0.0917 | |
| | 0.294 | 3.7 | 25000 | 0.1278 | 0.0894 | |
| | 0.2846 | 4.07 | 27500 | 0.1257 | 0.0885 | |
| | 0.259 | 4.44 | 30000 | 0.1244 | 0.0874 | |
| | 0.2348 | 4.81 | 32500 | 0.1245 | 0.0865 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.34.0 |
| - Pytorch 2.0.1 |
| - Datasets 2.14.5 |
| - Tokenizers 0.14.1 |
|
|
