| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| 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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6329 |
| - Accuracy: 0.6441 |
| - F1: 0.6528 |
| - Precision: 0.6402 |
| - Recall: 0.6658 |
|
|
| ## 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: 5.310370197342976e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 40 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 11 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.652 | 1.0 | 2221 | 0.6470 | 0.6087 | 0.5218 | 0.6759 | 0.4249 | |
| | 0.6283 | 2.0 | 4442 | 0.6329 | 0.6441 | 0.6528 | 0.6402 | 0.6658 | |
| | 0.5689 | 3.0 | 6663 | 0.6334 | 0.6371 | 0.6788 | 0.6112 | 0.7631 | |
| | 0.4785 | 4.0 | 8884 | 0.8592 | 0.6256 | 0.6131 | 0.6376 | 0.5905 | |
| | 0.3792 | 5.0 | 11105 | 0.9728 | 0.6207 | 0.6098 | 0.6310 | 0.5901 | |
| | 0.2839 | 6.0 | 13326 | 1.0226 | 0.6083 | 0.6212 | 0.6041 | 0.6394 | |
| | 0.2211 | 7.0 | 15547 | 1.6336 | 0.6145 | 0.6067 | 0.6223 | 0.5919 | |
| | 0.1756 | 8.0 | 17768 | 1.8340 | 0.6052 | 0.5951 | 0.6139 | 0.5773 | |
| | 0.1451 | 9.0 | 19989 | 2.0495 | 0.6078 | 0.5980 | 0.6165 | 0.5807 | |
| | 0.1147 | 10.0 | 22210 | 2.3889 | 0.6128 | 0.6128 | 0.6158 | 0.6098 | |
| | 0.0983 | 11.0 | 24431 | 2.4921 | 0.6119 | 0.6132 | 0.6141 | 0.6123 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.0.0 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
| |
