| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: FPC_model |
| | 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. --> |
| |
|
| | # FPC_model |
| | |
| | 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: 0.4029 |
| | - Accuracy: 0.9153 |
| | |
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 285 | 1.1683 | 0.7397 | |
| | | 1.5827 | 2.0 | 570 | 0.6301 | 0.8481 | |
| | | 1.5827 | 3.0 | 855 | 0.5046 | 0.8755 | |
| | | 0.4453 | 4.0 | 1140 | 0.4156 | 0.8941 | |
| | | 0.4453 | 5.0 | 1425 | 0.3790 | 0.9153 | |
| | | 0.1964 | 6.0 | 1710 | 0.3949 | 0.9078 | |
| | | 0.1964 | 7.0 | 1995 | 0.3969 | 0.9153 | |
| | | 0.1072 | 8.0 | 2280 | 0.4002 | 0.9153 | |
| | | 0.0611 | 9.0 | 2565 | 0.4027 | 0.9141 | |
| | | 0.0611 | 10.0 | 2850 | 0.4029 | 0.9153 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.0 |
| | - Tokenizers 0.13.3 |
| | |
