metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_us_reviews
metrics:
- accuracy
model-index:
- name: bert_category_prediction_amazon_book_reviews
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_us_reviews
type: amazon_us_reviews
config: Books_v1_00
split: train[:100]
args: Books_v1_00
metrics:
- name: Accuracy
type: accuracy
value: 0.6
bert_category_prediction_amazon_book_reviews
This model is a fine-tuned version of distilbert-base-uncased on the amazon_us_reviews dataset. It achieves the following results on the evaluation set:
- Loss: 1.3592
- Accuracy: 0.6
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 5 | 1.6152 | 0.6 |
| No log | 2.0 | 10 | 1.4903 | 0.6 |
| No log | 3.0 | 15 | 1.4141 | 0.6 |
| No log | 4.0 | 20 | 1.3729 | 0.6 |
| No log | 5.0 | 25 | 1.3592 | 0.6 |
Framework versions
- Transformers 4.28.0
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3