Exp23 Directfit Unfrozen

--- library_name: transformers base_model: cyttic/exp22-exp2warm-directfit-frozen tags: - generated_from_trainer metrics: - wer model-index: - name: exp23-directfit-unfrozen results: [] --- # exp23-directfit-unfrozen This model is a fine-tuned version of [cyttic/exp22-exp2warm-directfit-frozen](https://huggingface.co/cyttic/exp22-exp2warm-directfit-frozen) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4588 - Cer: 0.0245 - Wer: 0.0647 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 0.1 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | Wer | |:-------------:|:------:|:-----:|:---------------:|:------:|:------:| | 1.2577 | 0.0424 | 2500 | 1.3378 | 0.1416 | 0.2986 | | 1.0413 | 0.0848 | 5000 | 1.2441 | 0.1150 | 0.2561 | | 0.8436 | 0.1272 | 7500 | 1.0854 | 0.0917 | 0.2106 | | 0.7762 | 0.1696 | 10000 | 0.9314 | 0.0735 | 0.1700 | | 0.7096 | 0.2120 | 12500 | 0.8954 | 0.0627 | 0.1534 | | 0.6205 | 0.2544 | 15000 | 0.7907 | 0.0550 | 0.1378 | | 0.5873 | 0.2968 | 17500 | 0.7408 | 0.0486 | 0.1215 | | 0.5504 | 0.3392 | 20000 | 0.6894 | 0.0427 | 0.1112 | | 0.4826 | 0.3816 | 22500 | 0.6537 | 0.0406 | 0.1042 | | 0.5224 | 0.4240 | 25000 | 0.6245 | 0.0380 | 0.0965 | | 0.4430 | 0.4664 | 27500 | 0.5866 | 0.0366 | 0.0933 | | 0.4219 | 0.5088 | 30000 | 0.5724 | 0.0340 | 0.0873 | | 0.3557 | 0.5512 | 32500 | 0.5586 | 0.0318 | 0.0849 | | 0.3866 | 0.5936 | 35000 | 0.5399 | 0.0328 | 0.0845 | | 0.3586 | 0.6360 | 37500 | 0.5267 | 0.0305 | 0.0793 | | 0.4009 | 0.6784 | 40000 | 0.5082 | 0.0301 | 0.0769 | | 0.3140 | 0.7208 | 42500 | 0.5011 | 0.0289 | 0.0740 | | 0.3435 | 0.7632 | 45000 | 0.4874 | 0.0276 | 0.0725 | | 0.3141 | 0.8056 | 47500 | 0.4807 | 0.0267 | 0.0691 | | 0.3200 | 0.8480 | 50000 | 0.4738 | 0.0267 | 0.0687 | | 0.3201 | 0.8904 | 52500 | 0.4682 | 0.0250 | 0.0664 | | 0.3314 | 0.9328 | 55000 | 0.4633 | 0.0249 | 0.0652 | | 0.3427 | 0.9752 | 57500 | 0.4604 | 0.0244 | 0.0648 | | 0.3020 | 1.0 | 58962 | 0.4588 | 0.0245 | 0.0647 | ### Framework versions - Transformers 5.12.1 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2