amazon-reviews-sentiment-distilbert-base-uncased-6000-samples

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

  • Loss: 0.6126
  • Accuracy: 0.7355
  • F1: 0.6587

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
No log 1.0 188 0.6172 0.7335 0.6516
No log 2.0 376 0.6126 0.7355 0.6587

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.0
  • Datasets 2.14.6.dev0
  • Tokenizers 0.13.3
Downloads last month
16
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for santiviquez/amazon-reviews-sentiment-distilbert-base-uncased-6000-samples

Finetuned
(6838)
this model

Dataset used to train santiviquez/amazon-reviews-sentiment-distilbert-base-uncased-6000-samples

Evaluation results