--- license: cc-by-nc-4.0 base_model: utter-project/mHuBERT-147 tags: - generated_from_trainer datasets: - common_voice_17_0 metrics: - wer model-index: - name: mHuBERT-147-upper-sorbian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_17_0 type: common_voice_17_0 config: hsb split: validation args: hsb metrics: - name: Wer type: wer value: 1.0 --- [Visualize in Weights & Biases](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-new/runs/oduf7onr) # mHuBERT-147-upper-sorbian This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_17_0 dataset. It achieves the following results on the evaluation set: - Loss: 3.2172 - Wer: 1.0 - Cer: 1.0 ## 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: 0.001 - 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: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-------:|:----:|:---------------:|:---:|:---:| | 4.0738 | 3.9216 | 100 | 4.0797 | 1.0 | 1.0 | | 3.223 | 7.8431 | 200 | 3.2273 | 1.0 | 1.0 | | 3.1741 | 11.7647 | 300 | 3.2232 | 1.0 | 1.0 | | 3.2292 | 15.6863 | 400 | 3.2237 | 1.0 | 1.0 | | 3.2105 | 19.6078 | 500 | 3.2269 | 1.0 | 1.0 | | 3.1911 | 23.5294 | 600 | 3.2202 | 1.0 | 1.0 | | 3.2626 | 27.4510 | 700 | 3.2177 | 1.0 | 1.0 | | 3.21 | 31.3725 | 800 | 3.2232 | 1.0 | 1.0 | | 3.1871 | 35.2941 | 900 | 3.2211 | 1.0 | 1.0 | | 3.2224 | 39.2157 | 1000 | 3.2249 | 1.0 | 1.0 | | 3.2408 | 43.1373 | 1100 | 3.2215 | 1.0 | 1.0 | | 3.2 | 47.0588 | 1200 | 3.2193 | 1.0 | 1.0 | | 3.202 | 50.9804 | 1300 | 3.2181 | 1.0 | 1.0 | | 3.2286 | 54.9020 | 1400 | 3.2190 | 1.0 | 1.0 | | 3.1863 | 58.8235 | 1500 | 3.2187 | 1.0 | 1.0 | | 3.1868 | 62.7451 | 1600 | 3.2174 | 1.0 | 1.0 | | 3.226 | 66.6667 | 1700 | 3.2199 | 1.0 | 1.0 | | 3.1944 | 70.5882 | 1800 | 3.2195 | 1.0 | 1.0 | | 3.1997 | 74.5098 | 1900 | 3.2180 | 1.0 | 1.0 | | 3.2184 | 78.4314 | 2000 | 3.2200 | 1.0 | 1.0 | | 3.2252 | 82.3529 | 2100 | 3.2189 | 1.0 | 1.0 | | 3.208 | 86.2745 | 2200 | 3.2176 | 1.0 | 1.0 | | 3.2122 | 90.1961 | 2300 | 3.2170 | 1.0 | 1.0 | | 3.2307 | 94.1176 | 2400 | 3.2169 | 1.0 | 1.0 | | 3.1852 | 98.0392 | 2500 | 3.2172 | 1.0 | 1.0 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.3.1+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1