| --- |
| license: apache-2.0 |
| base_model: allenai/longformer-base-4096 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: patentClassfication2 |
| 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. --> |
|
|
| # patentClassfication2 |
|
|
| This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6892 |
| - Accuracy: 0.5443 |
| - F1: 0.7049 |
| - Precision: 0.5443 |
| - Recall: 1.0 |
|
|
| ## 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: 0.00010736040521746779 |
| - train_batch_size: 2 |
| - eval_batch_size: 4 |
| - seed: 51 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.6904 | 1.0 | 4992 | 0.6893 | 0.5443 | 0.7049 | 0.5443 | 1.0 | |
| | 0.6892 | 2.0 | 9985 | 0.6982 | 0.5443 | 0.7049 | 0.5443 | 1.0 | |
| | 0.6916 | 3.0 | 14977 | 0.6892 | 0.5443 | 0.7049 | 0.5443 | 1.0 | |
| | 0.6877 | 4.0 | 19970 | 0.6900 | 0.5443 | 0.7049 | 0.5443 | 1.0 | |
| | 0.6878 | 5.0 | 24960 | 0.6901 | 0.5443 | 0.7049 | 0.5443 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.0.0 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
| |
