Push ../models/xlnet/xlnet-base-cased/biored-augmentations-only/ trained on biored-train_160_splits.pt (160 samples)
8a7fc69
verified
| language: | |
| - en | |
| license: mit | |
| base_model: xlnet-base-cased | |
| tags: | |
| - low-resource NER | |
| - token_classification | |
| - biomedicine | |
| - medical NER | |
| - generated_from_trainer | |
| datasets: | |
| - medicine | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: Dagobert42/xlnet-base-cased-biored-augmented | |
| 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. --> | |
| # Dagobert42/xlnet-base-cased-biored-augmented | |
| This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the bigbio/biored dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1510 | |
| - Accuracy: 0.9508 | |
| - Precision: 0.8521 | |
| - Recall: 0.8278 | |
| - F1: 0.8391 | |
| - Weighted F1: 0.9506 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 50 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:| | |
| | No log | 1.0 | 20 | 0.2068 | 0.9335 | 0.8641 | 0.7475 | 0.7976 | 0.9312 | | |
| | No log | 2.0 | 40 | 0.1962 | 0.939 | 0.8035 | 0.8046 | 0.8013 | 0.9382 | | |
| | No log | 3.0 | 60 | 0.1965 | 0.9429 | 0.8654 | 0.7947 | 0.826 | 0.9415 | | |
| | No log | 4.0 | 80 | 0.1964 | 0.9443 | 0.8279 | 0.8174 | 0.8218 | 0.9436 | | |
| ### Framework versions | |
| - Transformers 4.35.2 | |
| - Pytorch 2.0.1+cu117 | |
| - Datasets 2.18.0 | |
| - Tokenizers 0.15.0 | |