metadata
tags:
- generated_from_trainer
datasets:
- yelp_review_full
metrics:
- accuracy
model-index:
- name: yelp_review_rating_reberta_base
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yelp_review_full
type: yelp_review_full
config: yelp_review_full
split: train
args: yelp_review_full
metrics:
- name: Accuracy
type: accuracy
value: 0.67086
yelp_review_rating_reberta_base
This model was trained from scratch on the yelp_review_full dataset. It achieves the following results on the evaluation set:
- Loss: 0.8071
- Accuracy: 0.6709
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.8355 | 1.0 | 40625 | 0.6449 | 0.8211 |
| 0.7709 | 2.0 | 81250 | 0.6615 | 0.7877 |
| 0.7141 | 3.0 | 121875 | 0.6712 | 0.7689 |
| 0.6511 | 4.0 | 162500 | 0.6724 | 0.7845 |
| 0.6229 | 5.0 | 203125 | 0.6719 | 0.8009 |
| 0.6036 | 6.0 | 243750 | 0.8071 | 0.6709 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu102
- Datasets 2.6.1
- Tokenizers 0.12.1