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: 0.6819221967963387
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: 0.9536
- Accuracy: 0.5767
- F1: [0.62380713 0.45806452 0.5077951 0.56106774 0.73541247]
- Precision: [0.62537764 0.45920398 0.49326923 0.58508403 0.72376238]
- Recall: [0.62224449 0.45693069 0.52320245 0.53894533 0.74744376]
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 |
|---|---|---|---|---|---|---|---|
| 0.9704 | 1.0 | 2813 | 0.9536 | 0.5767 | [0.62380713 0.45806452 0.5077951 0.56106774 0.73541247] | [0.62537764 0.45920398 0.49326923 0.58508403 0.72376238] | [0.62224449 0.45693069 0.52320245 0.53894533 0.74744376] |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1