--- license: mit base_model: microsoft/deberta-v3-small tags: - generated_from_trainer model-index: - name: deberta-v3-small-sp500-edgar-10k-markdown-1024-vN results: [] --- # deberta-v3-small-sp500-edgar-10k-markdown-1024-vN This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0005 - Mse: 0.0005 ## 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: 4 - eval_batch_size: 4 - seed: 30826 - gradient_accumulation_steps: 16 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Mse | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0064 | 0.54 | 50 | 0.0006 | 0.0006 | | 0.0043 | 1.08 | 100 | 0.0005 | 0.0005 | | 0.0028 | 1.61 | 150 | 0.0006 | 0.0006 | | 0.0025 | 2.15 | 200 | 0.0005 | 0.0005 | | 0.0025 | 2.69 | 250 | 0.0005 | 0.0005 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.2.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.2