--- license: apache-2.0 base_model: smutuvi/wav2vec2-large-xlsr-sw tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-large-xlsr-sw_ndizi_782_100_epochs results: [] --- # wav2vec2-large-xlsr-sw_ndizi_782_100_epochs This model is a fine-tuned version of [smutuvi/wav2vec2-large-xlsr-sw](https://huggingface.co/smutuvi/wav2vec2-large-xlsr-sw) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.1009 - Wer: 0.4847 ## 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: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.4035 | 4.79 | 400 | 1.2492 | 0.5608 | | 0.8489 | 9.58 | 800 | 1.0208 | 0.5114 | | 0.632 | 14.37 | 1200 | 1.3292 | 0.5306 | | 0.4653 | 19.16 | 1600 | 1.5159 | 0.5109 | | 0.3598 | 23.95 | 2000 | 1.4650 | 0.5450 | | 0.2776 | 28.74 | 2400 | 1.8568 | 0.5124 | | 0.218 | 33.53 | 2800 | 2.0913 | 0.5188 | | 0.1711 | 38.32 | 3200 | 2.2706 | 0.5035 | | 0.141 | 43.11 | 3600 | 2.3050 | 0.5094 | | 0.1162 | 47.9 | 4000 | 2.4539 | 0.5025 | | 0.1007 | 52.69 | 4400 | 2.4754 | 0.5020 | | 0.0881 | 57.49 | 4800 | 2.5512 | 0.5030 | | 0.0816 | 62.28 | 5200 | 2.6458 | 0.5064 | | 0.0792 | 67.07 | 5600 | 2.7869 | 0.5025 | | 0.06 | 71.86 | 6000 | 2.9063 | 0.5040 | | 0.0594 | 76.65 | 6400 | 2.8363 | 0.5049 | | 0.0527 | 81.44 | 6800 | 3.0801 | 0.4921 | | 0.0473 | 86.23 | 7200 | 3.0959 | 0.4867 | | 0.0471 | 91.02 | 7600 | 3.0942 | 0.4852 | | 0.0405 | 95.81 | 8000 | 3.1009 | 0.4847 | ### Framework versions - Transformers 4.37.1 - Pytorch 2.2.1+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0