| --- |
| license: apache-2.0 |
| language: eu |
| metrics: |
| - wer |
| - cer |
| tags: |
| - automatic-speech-recognition |
| - basque |
| - generated_from_trainer |
| - hf-asr-leaderboard |
| - robust-speech-event |
| datasets: |
| - mozilla-foundation/common_voice_7_0 |
| model-index: |
| - name: wav2vec2-large-xls-r-300m-basque |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 7 |
| type: mozilla-foundation/common_voice_7_0 |
| args: eu |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 51.89 |
| - name: Test CER |
| type: cer |
| value: 10.01 |
| --- |
| |
| <!-- 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. --> |
|
|
| # wav2vec2-large-xls-r-300m-basque |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4276 |
| - Wer: 0.5962 |
| |
| ## 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: 0.0003 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 4 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 3.9902 | 1.29 | 400 | 2.1257 | 1.0 | |
| | 0.9625 | 2.59 | 800 | 0.5695 | 0.7452 | |
| | 0.4605 | 3.88 | 1200 | 0.4276 | 0.5962 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.16.2 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 1.18.3 |
| - Tokenizers 0.11.0 |
| |
