README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: distilbert-amazon-shoe-reviews
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          type: amazon_us_reviews
          name: Amazon US reviews
          split: Shoes
        metrics:
          - type: accuracy
            value: 0.48
            name: Accuracy

distilbert-amazon-shoe-reviews

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: 1.3445
• Accuracy: 0.48
• F1: [0. 0. 0. 0. 0.64864865]
• Precision: [0. 0. 0. 0. 0.48]
• Recall: [0. 0. 0. 0. 1.]

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: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	15	1.3445	0.48	[0. 0. 0. 0. 0.64864865]	[0. 0. 0. 0. 0.48]	[0. 0. 0. 0. 1.]

Framework versions

• Transformers 4.19.4
• Pytorch 1.11.0
• Datasets 2.3.2
• Tokenizers 0.12.1