metadata

license: mit
base_model: nlptown/bert-base-multilingual-uncased-sentiment
tags:
  - generated_from_trainer
datasets:
  - amazon_reviews_multi
metrics:
  - accuracy
  - f1
model-index:
  - name: amazon-reviews-finetuning-distilbert-base-uncased
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: amazon_reviews_multi
          type: amazon_reviews_multi
          config: en
          split: validation
          args: en
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7564102564102564
          - name: F1
            type: f1
            value: 0.7100768898860667

amazon-reviews-finetuning-distilbert-base-uncased

This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:

Loss: 0.6269
Accuracy: 0.7564
F1: 0.7101

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	94	0.6012	0.7532	0.6974
No log	2.0	188	0.6269	0.7564	0.7101

Framework versions

Transformers 4.33.2
Pytorch 2.0.0
Datasets 2.14.6.dev0
Tokenizers 0.13.3