MSP Visual

--- library_name: transformers tags: - generated_from_trainer metrics: - wer model-index: - name: MSP-Visual results: [] --- # MSP-Visual This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3334 - Wer: 0.6493 - Cer: 0.3725 ## 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: 0.0001 - train_batch_size: 32 - eval_batch_size: 32 - 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: cosine - lr_scheduler_warmup_steps: 1000.0 - training_steps: 20000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| | 2.5771 | 0.05 | 1000 | 2.3988 | 0.9791 | 0.6114 | | 2.0987 | 0.1 | 2000 | 1.7770 | 0.8288 | 0.4786 | | 1.9764 | 0.15 | 3000 | 1.6459 | 0.7827 | 0.4485 | | 1.9493 | 0.2 | 4000 | 1.6139 | 0.7614 | 0.4388 | | 1.9069 | 0.25 | 5000 | 1.5498 | 0.7351 | 0.4191 | | 1.9144 | 0.3 | 6000 | 1.5212 | 0.7212 | 0.4142 | | 1.8289 | 0.35 | 7000 | 1.4857 | 0.7139 | 0.4063 | | 1.8845 | 0.4 | 8000 | 1.4832 | 0.6958 | 0.3979 | | 1.7763 | 0.45 | 9000 | 1.4466 | 0.6938 | 0.3946 | | 1.9370 | 0.5 | 10000 | 1.4235 | 0.6825 | 0.3916 | | 1.7678 | 0.55 | 11000 | 1.4164 | 0.6784 | 0.3857 | | 1.8403 | 0.6 | 12000 | 1.3981 | 0.6696 | 0.3868 | | 1.6723 | 0.65 | 13000 | 1.3849 | 0.6631 | 0.3769 | | 1.7040 | 0.7 | 14000 | 1.3884 | 0.6579 | 0.3763 | | 1.5821 | 0.75 | 15000 | 1.3599 | 0.6588 | 0.3756 | | 1.5721 | 0.8 | 16000 | 1.3480 | 0.6519 | 0.3728 | | 1.6635 | 0.85 | 17000 | 1.3432 | 0.6527 | 0.3732 | | 1.6557 | 0.9 | 18000 | 1.3501 | 0.6525 | 0.3748 | | 1.7992 | 0.95 | 19000 | 1.3334 | 0.6493 | 0.3725 | | 1.7090 | 1.0 | 20000 | 1.3328 | 0.6499 | 0.3724 | ### Framework versions - Transformers 5.10.2 - Pytorch 2.8.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2