--- license: apache-2.0 tags: - generated_from_trainer datasets: - mirfan899/kids_phoneme_sm base_model: facebook/wav2vec2-large-xlsr-53 model-index: - name: kids_phoneme_sm_model results: [] --- # kids_phoneme_sm_model This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the https://huggingface.co/datasets/mirfan899/kids_phoneme_sm dataset. It achieves the following results on the evaluation set: - Loss: 0.5405 - Cer: 0.2770 ## 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: 4e-05 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 3.2595 | 0.74 | 500 | 3.7094 | 1.0 | | 2.8393 | 1.48 | 1000 | 3.2563 | 1.0 | | 2.7916 | 2.22 | 1500 | 3.0450 | 1.0 | | 1.9585 | 2.96 | 2000 | 1.0280 | 0.8428 | | 1.0099 | 3.7 | 2500 | 0.6477 | 0.5162 | | 0.7968 | 4.44 | 3000 | 0.5551 | 0.4592 | | 0.6977 | 5.19 | 3500 | 0.5107 | 0.4065 | | 0.609 | 5.93 | 4000 | 0.4763 | 0.3916 | | 0.5941 | 6.67 | 4500 | 0.4817 | 0.3850 | | 0.5411 | 7.41 | 5000 | 0.4755 | 0.3639 | | 0.5021 | 8.15 | 5500 | 0.4649 | 0.3622 | | 0.4884 | 8.89 | 6000 | 0.4630 | 0.3569 | | 0.4484 | 9.63 | 6500 | 0.4675 | 0.3420 | | 0.4432 | 10.37 | 7000 | 0.4192 | 0.3402 | | 0.399 | 11.11 | 7500 | 0.4508 | 0.3310 | | 0.4215 | 11.85 | 8000 | 0.4406 | 0.3345 | | 0.366 | 12.59 | 8500 | 0.4620 | 0.3248 | | 0.3708 | 13.33 | 9000 | 0.4594 | 0.3327 | | 0.3352 | 14.07 | 9500 | 0.4649 | 0.3121 | | 0.3468 | 14.81 | 10000 | 0.4413 | 0.3020 | | 0.3283 | 15.56 | 10500 | 0.4948 | 0.2915 | | 0.3222 | 16.3 | 11000 | 0.4870 | 0.3025 | | 0.3081 | 17.04 | 11500 | 0.4779 | 0.2919 | | 0.3099 | 17.78 | 12000 | 0.4927 | 0.2871 | | 0.2485 | 18.52 | 12500 | 0.5013 | 0.2831 | | 0.3163 | 19.26 | 13000 | 0.4929 | 0.2888 | | 0.2555 | 20.0 | 13500 | 0.5234 | 0.2888 | | 0.2705 | 20.74 | 14000 | 0.5259 | 0.2818 | | 0.2632 | 21.48 | 14500 | 0.5105 | 0.2831 | | 0.2374 | 22.22 | 15000 | 0.5284 | 0.2845 | | 0.2565 | 22.96 | 15500 | 0.5237 | 0.2875 | | 0.2394 | 23.7 | 16000 | 0.5368 | 0.2818 | | 0.2458 | 24.44 | 16500 | 0.5386 | 0.2814 | | 0.2383 | 25.19 | 17000 | 0.5366 | 0.2788 | | 0.2152 | 25.93 | 17500 | 0.5320 | 0.2770 | | 0.231 | 26.67 | 18000 | 0.5441 | 0.2779 | | 0.2061 | 27.41 | 18500 | 0.5448 | 0.2796 | | 0.245 | 28.15 | 19000 | 0.5413 | 0.2796 | | 0.2119 | 28.89 | 19500 | 0.5379 | 0.2774 | | 0.2155 | 29.63 | 20000 | 0.5405 | 0.2770 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.0.0 - Datasets 2.13.0 - Tokenizers 0.13.3