| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| base_model: distilbert-base-uncased | |
| model-index: | |
| - name: distilbert-base-uncased-finetuned-fashion | |
| 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-finetuned-fashion | |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on a munally created dataset in order to detect fashion (label_0) from non-fashion (label_1) items. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0809 | |
| - Accuracy: 0.98 | |
| - F1: 0.9801 | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 2e-05 | |
| - train_batch_size: 64 | |
| - eval_batch_size: 64 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 0.4017 | 1.0 | 47 | 0.1220 | 0.966 | 0.9662 | | |
| | 0.115 | 2.0 | 94 | 0.0809 | 0.98 | 0.9801 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |