| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: ec_classfication |
| 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. --> |
|
|
| # ec_classfication |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6543 |
| - F1: 0.7609 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 31 | 0.6418 | 0.4262 | |
| | No log | 2.0 | 62 | 0.4992 | 0.7342 | |
| | No log | 3.0 | 93 | 0.4732 | 0.7879 | |
| | No log | 4.0 | 124 | 0.4817 | 0.7089 | |
| | No log | 5.0 | 155 | 0.4872 | 0.7742 | |
| | No log | 6.0 | 186 | 0.5026 | 0.7872 | |
| | No log | 7.0 | 217 | 0.5202 | 0.7778 | |
| | No log | 8.0 | 248 | 0.5280 | 0.7711 | |
| | No log | 9.0 | 279 | 0.5629 | 0.75 | |
| | No log | 10.0 | 310 | 0.6319 | 0.7872 | |
| | No log | 11.0 | 341 | 0.6363 | 0.7872 | |
| | No log | 12.0 | 372 | 0.6850 | 0.7708 | |
| | No log | 13.0 | 403 | 0.6702 | 0.7872 | |
| | No log | 14.0 | 434 | 0.6495 | 0.7692 | |
| | No log | 15.0 | 465 | 0.6543 | 0.7609 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.27.3 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.2 |
| |
