metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: amazon_review_classification
results: []
amazon_review_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: 1.3976
- Accuracy: 0.6732
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 115 | 1.0703 | 0.6732 |
| No log | 2.0 | 230 | 1.2393 | 0.6341 |
| No log | 3.0 | 345 | 1.1084 | 0.6683 |
| No log | 4.0 | 460 | 1.1262 | 0.6829 |
| 0.3201 | 5.0 | 575 | 1.3179 | 0.6732 |
| 0.3201 | 6.0 | 690 | 1.3832 | 0.6585 |
| 0.3201 | 7.0 | 805 | 1.2997 | 0.6683 |
| 0.3201 | 8.0 | 920 | 1.3872 | 0.6634 |
| 0.0863 | 9.0 | 1035 | 1.3832 | 0.6634 |
| 0.0863 | 10.0 | 1150 | 1.3976 | 0.6732 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2