| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased_fold_8_binary_v1 |
| 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_8_binary_v1 |
|
|
| 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: 1.6283 |
| - F1: 0.8178 |
|
|
| ## 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 | 0.4038 | 0.7981 | |
| | 0.409 | 2.0 | 580 | 0.4023 | 0.8176 | |
| | 0.409 | 3.0 | 870 | 0.5245 | 0.8169 | |
| | 0.1938 | 4.0 | 1160 | 0.6242 | 0.8298 | |
| | 0.1938 | 5.0 | 1450 | 0.8432 | 0.8159 | |
| | 0.0848 | 6.0 | 1740 | 1.0887 | 0.8015 | |
| | 0.038 | 7.0 | 2030 | 1.0700 | 0.8167 | |
| | 0.038 | 8.0 | 2320 | 1.0970 | 0.8241 | |
| | 0.0159 | 9.0 | 2610 | 1.2474 | 0.8142 | |
| | 0.0159 | 10.0 | 2900 | 1.3453 | 0.8184 | |
| | 0.01 | 11.0 | 3190 | 1.4412 | 0.8147 | |
| | 0.01 | 12.0 | 3480 | 1.4263 | 0.8181 | |
| | 0.007 | 13.0 | 3770 | 1.3859 | 0.8258 | |
| | 0.0092 | 14.0 | 4060 | 1.4633 | 0.8128 | |
| | 0.0092 | 15.0 | 4350 | 1.4304 | 0.8206 | |
| | 0.0096 | 16.0 | 4640 | 1.5081 | 0.8149 | |
| | 0.0096 | 17.0 | 4930 | 1.5239 | 0.8189 | |
| | 0.0047 | 18.0 | 5220 | 1.5268 | 0.8151 | |
| | 0.0053 | 19.0 | 5510 | 1.5445 | 0.8173 | |
| | 0.0053 | 20.0 | 5800 | 1.6051 | 0.8180 | |
| | 0.0014 | 21.0 | 6090 | 1.5981 | 0.8211 | |
| | 0.0014 | 22.0 | 6380 | 1.5957 | 0.8225 | |
| | 0.001 | 23.0 | 6670 | 1.5838 | 0.8189 | |
| | 0.001 | 24.0 | 6960 | 1.6301 | 0.8178 | |
| | 0.0018 | 25.0 | 7250 | 1.6283 | 0.8178 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
