metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: product_classifier
results: []
product_classifier
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6760
- Accuracy: {'accuracy': 0.80125}
- Precision: {'precision': 0.785989926719994}
- Recall: {'recall': 0.7755906520102293}
- F1 Score: {'f1': 0.7704315421053631}
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|---|---|---|---|---|---|---|---|
| 0.9575 | 1.0 | 3200 | 0.6832 | {'accuracy': 0.7978125} | {'precision': 0.7851098622896849} | {'recall': 0.7737991362724596} | {'f1': 0.771520016712035} |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3