metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - yelp_review_full
metrics:
  - accuracy
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: distilbert-base-uncased-finetuned-yelp-reviews
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: yelp_review_full
          type: yelp_review_full
          config: yelp_review_full
          split: train
          args: yelp_review_full
        metrics:
          - type: accuracy
            value: 0.6418461538461538
            name: Accuracy
          - type: f1
            value: 0.6424942003355615
            name: F1

distilbert-base-uncased-finetuned-yelp-reviews

This model is a fine-tuned version of distilbert-base-uncased on the yelp_review_full dataset. It achieves the following results on the evaluation set:

Loss: 0.8288
Accuracy: 0.6418
F1: 0.6425

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: 32
eval_batch_size: 32
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
0.8991	1.0	1524	0.8396	0.6302	0.6294
0.754	2.0	3048	0.8288	0.6418	0.6425

Framework versions

Transformers 4.21.2
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1