| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: MiniLM-evidence-types | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # MiniLM-evidence-types | |
| This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.3612 | |
| - Macro f1: 0.1900 | |
| - Weighted f1: 0.5901 | |
| - Accuracy: 0.6499 | |
| - Balanced accuracy: 0.2161 | |
| ## 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: 3e-05 | |
| - train_batch_size: 32 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 1 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Macro f1 | Weighted f1 | Accuracy | Balanced accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:-----------------:| | |
| | 1.5 | 1.0 | 125 | 1.3612 | 0.1900 | 0.5901 | 0.6499 | 0.2161 | | |
| ### Framework versions | |
| - Transformers 4.19.2 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.2.2 | |
| - Tokenizers 0.12.1 | |