metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: distilbert_amazon_book_classification
results: []
distilbert_amazon_book_classification
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4475
- Accuracy: 0.5871
- F1 Score: 0.5865
- Precision: 0.5967
- Recall: 0.5871
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.6436 | 0.9999 | 9679 | 1.4688 | 0.5680 | 0.5624 | 0.5822 | 0.5680 |
| 1.0845 | 1.9998 | 19358 | 1.4475 | 0.5871 | 0.5865 | 0.5967 | 0.5871 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 4.1.1
- Tokenizers 0.20.1