distilbert-base-uncased-finetuned-fashion
This model is a fine-tuned version of 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
- Downloads last month
- 27
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for rasta/distilbert-base-uncased-finetuned-fashion
Base model
distilbert/distilbert-base-uncased