| --- |
| license: mit |
| base_model: facebook/w2v-bert-2.0 |
| tags: |
| - generated_from_trainer |
| - asr |
| - w2v-bert-2.0 |
| datasets: |
| - common_voice_16_1 |
| metrics: |
| - wer |
| - cer |
| - bertscore |
| model-index: |
| - name: w2v-bert-2.0-pt_pt_v2 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: common_voice_16_1 |
| type: common_voice_16_1 |
| config: pt |
| split: validation |
| args: pt |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.08315087821729188 |
| language: |
| - pt |
| --- |
| |
| <!-- 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. --> |
|
|
| # w2v-bert-2.0-pt_pt_v2 |
|
|
| This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_1 Portuguese subset using 1XRTX 3090. |
| It achieves the following results on the test set: |
| - Wer: 0.10491320595991134 |
| - Cer: 0.032070871626631914 |
| - Bert Score: 0.9619712047981167 |
| - Sentence Similarity: 0.93867844 |
| |
| ## 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: 5e-05 |
| - 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: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bert Score | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:----------:| |
| | 1.2735 | 1.0 | 678 | 0.2292 | 0.1589 | 0.0415 | 0.9498 | |
| | 0.1715 | 2.0 | 1356 | 0.1762 | 0.1283 | 0.0344 | 0.9599 | |
| | 0.1158 | 3.0 | 2034 | 0.1539 | 0.1100 | 0.0298 | 0.9646 | |
| | 0.0821 | 4.0 | 2712 | 0.1362 | 0.0949 | 0.0258 | 0.9703 | |
| | 0.0605 | 5.0 | 3390 | 0.1349 | 0.0860 | 0.0236 | 0.9728 | |
| | 0.0475 | 6.0 | 4068 | 0.1395 | 0.0871 | 0.0239 | 0.9728 | |
| | 0.0355 | 7.0 | 4746 | 0.1487 | 0.0837 | 0.0230 | 0.9739 | |
| | 0.0309 | 8.0 | 5424 | 0.1452 | 0.0873 | 0.0240 | 0.9728 | |
| | 0.0308 | 9.0 | 6102 | 0.1390 | 0.0843 | 0.0228 | 0.9735 | |
| | 0.0239 | 10.0 | 6780 | 0.1282 | 0.0832 | 0.0224 | 0.9739 | |
| |
| ### Evaluation results |
| |
| | Test Wer | Test Cer | Test Bert Score | Runtime | Samples per second | |
| |:------------------:|:-------------------:|:-----------------:|:-------:|:---------------------:| |
| | 0.09146400542583083| 0.02643665913309742 | 0.9702128323433327| 266.8185| 35.282 | |
| |
| ### Framework versions |
| |
| - Transformers 4.38.2 |
| - Pytorch 2.2.0 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
