--- license: mit base_model: facebook/w2v-bert-2.0 tags: - generated_from_trainer datasets: - common_voice_8_0 metrics: - wer model-index: - name: w2v-bert-2.0-Swahili-CV-train-8.0 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_8_0 type: common_voice_8_0 config: sw split: test args: sw metrics: - name: Wer type: wer value: 0.17621560728323557 --- # w2v-bert-2.0-Swahili-CV-train-8.0 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_8_0 dataset. It achieves the following results on the evaluation set: - Loss: inf - Wer: 0.1762 ## 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: 64 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 128 - 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 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.3054 | 1.95 | 300 | inf | 0.1116 | | 0.1079 | 3.91 | 600 | inf | 0.1036 | | 0.0821 | 5.86 | 900 | inf | 0.0918 | | 0.0959 | 7.82 | 1200 | inf | 0.2150 | | 0.3709 | 9.77 | 1500 | inf | 0.1762 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1+cu121 - Datasets 2.17.0 - Tokenizers 0.15.2