README.md

metadata

license: apache-2.0
base_model: bert-base-cased
tags:
  - generated_from_trainer
datasets:
  - yelp_review_full
metrics:
  - accuracy
model-index:
  - name: bbc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: yelp_review_full
          type: yelp_review_full
          config: yelp_review_full
          split: test
          args: yelp_review_full
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.499

bbc

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

• Loss: 1.1692
• Accuracy: 0.499

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: 5e-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	1.4265	0.391
1.4806	2.0	500	1.2233	0.458
1.4806	3.0	750	1.1692	0.499

Framework versions

• Transformers 4.32.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3