| | --- |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: results |
| | 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. --> |
| |
|
| | # results |
| |
|
| | 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: 2.9905 |
| | - Accuracy: 0.5067 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 30 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 132 | 0.6630 | 0.6267 | |
| | | No log | 2.0 | 264 | 0.6697 | 0.6267 | |
| | | No log | 3.0 | 396 | 0.6605 | 0.6267 | |
| | | 0.6686 | 4.0 | 528 | 0.6797 | 0.6267 | |
| | | 0.6686 | 5.0 | 660 | 0.6599 | 0.5733 | |
| | | 0.6686 | 6.0 | 792 | 0.6702 | 0.58 | |
| | | 0.6686 | 7.0 | 924 | 0.7593 | 0.5267 | |
| | | 0.6278 | 8.0 | 1056 | 0.7622 | 0.6 | |
| | | 0.6278 | 9.0 | 1188 | 0.8147 | 0.6067 | |
| | | 0.6278 | 10.0 | 1320 | 1.2285 | 0.5733 | |
| | | 0.6278 | 11.0 | 1452 | 1.2681 | 0.58 | |
| | | 0.5453 | 12.0 | 1584 | 1.4571 | 0.5667 | |
| | | 0.5453 | 13.0 | 1716 | 1.5210 | 0.5467 | |
| | | 0.5453 | 14.0 | 1848 | 1.6548 | 0.5733 | |
| | | 0.5453 | 15.0 | 1980 | 1.6931 | 0.5667 | |
| | | 0.4703 | 16.0 | 2112 | 1.8606 | 0.5867 | |
| | | 0.4703 | 17.0 | 2244 | 1.9779 | 0.56 | |
| | | 0.4703 | 18.0 | 2376 | 2.3998 | 0.4933 | |
| | | 0.3567 | 19.0 | 2508 | 2.2930 | 0.5 | |
| | | 0.3567 | 20.0 | 2640 | 2.6606 | 0.4933 | |
| | | 0.3567 | 21.0 | 2772 | 2.4945 | 0.4933 | |
| | | 0.3567 | 22.0 | 2904 | 2.6740 | 0.5133 | |
| | | 0.2371 | 23.0 | 3036 | 2.7472 | 0.5 | |
| | | 0.2371 | 24.0 | 3168 | 2.7916 | 0.5 | |
| | | 0.2371 | 25.0 | 3300 | 2.8399 | 0.5 | |
| | | 0.2371 | 26.0 | 3432 | 2.8665 | 0.52 | |
| | | 0.1688 | 27.0 | 3564 | 2.9246 | 0.5133 | |
| | | 0.1688 | 28.0 | 3696 | 2.9675 | 0.5 | |
| | | 0.1688 | 29.0 | 3828 | 2.9967 | 0.5067 | |
| | | 0.1688 | 30.0 | 3960 | 2.9905 | 0.5067 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
