| | --- |
| | base_model: allenai/scibert_scivocab_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 [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6263 |
| | - Accuracy: 0.6572 |
| | - F1: 0.6151 |
| | - Precision: 0.6966 |
| | - Recall: 0.5507 |
| |
|
| | ## 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: 2.54241e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 41 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - lr_scheduler_warmup_steps: 24 |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 0.6346 | 1.0 | 4438 | 0.6263 | 0.6572 | 0.6151 | 0.6966 | 0.5507 | |
| | | 0.5796 | 2.0 | 8876 | 0.6388 | 0.6758 | 0.6833 | 0.6646 | 0.7030 | |
| | | 0.5268 | 3.0 | 13314 | 0.6567 | 0.6715 | 0.6833 | 0.6565 | 0.7123 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
