| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_6_binary |
| 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. --> |
|
|
| # distilbert-base-uncased_fold_6_binary |
| |
| 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: 1.6838 |
| - F1: 0.7881 |
| |
| ## 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: 25 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 290 | 0.4181 | 0.7732 | |
| | 0.4097 | 2.0 | 580 | 0.3967 | 0.7697 | |
| | 0.4097 | 3.0 | 870 | 0.5811 | 0.7797 | |
| | 0.2034 | 4.0 | 1160 | 0.8684 | 0.7320 | |
| | 0.2034 | 5.0 | 1450 | 0.9116 | 0.7718 | |
| | 0.0794 | 6.0 | 1740 | 1.0588 | 0.7690 | |
| | 0.0278 | 7.0 | 2030 | 1.2092 | 0.7738 | |
| | 0.0278 | 8.0 | 2320 | 1.2180 | 0.7685 | |
| | 0.0233 | 9.0 | 2610 | 1.3005 | 0.7676 | |
| | 0.0233 | 10.0 | 2900 | 1.4009 | 0.7634 | |
| | 0.0093 | 11.0 | 3190 | 1.4528 | 0.7805 | |
| | 0.0093 | 12.0 | 3480 | 1.4803 | 0.7859 | |
| | 0.0088 | 13.0 | 3770 | 1.4775 | 0.7750 | |
| | 0.0077 | 14.0 | 4060 | 1.6171 | 0.7699 | |
| | 0.0077 | 15.0 | 4350 | 1.6429 | 0.7636 | |
| | 0.0047 | 16.0 | 4640 | 1.5619 | 0.7819 | |
| | 0.0047 | 17.0 | 4930 | 1.5833 | 0.7724 | |
| | 0.0034 | 18.0 | 5220 | 1.6400 | 0.7853 | |
| | 0.0008 | 19.0 | 5510 | 1.6508 | 0.7792 | |
| | 0.0008 | 20.0 | 5800 | 1.6838 | 0.7881 | |
| | 0.0009 | 21.0 | 6090 | 1.6339 | 0.7829 | |
| | 0.0009 | 22.0 | 6380 | 1.6824 | 0.7806 | |
| | 0.0016 | 23.0 | 6670 | 1.6867 | 0.7876 | |
| | 0.0016 | 24.0 | 6960 | 1.7107 | 0.7877 | |
| | 0.0013 | 25.0 | 7250 | 1.6933 | 0.7812 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
