metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- yelp_review_full
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yelp_review_full
type: yelp_review_full
config: yelp_review_full
split: test
args: yelp_review_full
metrics:
- name: Accuracy
type: accuracy
value: 0.564
- name: F1
type: f1
value: 0.5645870203957494
distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the yelp_review_full dataset. It achieves the following results on the evaluation set:
- Loss: 3.7507
- Accuracy: 0.564
- F1: 0.5646
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6971 | 1.0 | 1625 | 1.2672 | 0.57 | 0.5725 |
| 0.6236 | 2.0 | 3250 | 1.4192 | 0.546 | 0.5465 |
| 0.5152 | 3.0 | 4875 | 2.2110 | 0.556 | 0.5514 |
| 0.3756 | 4.0 | 6500 | 2.7943 | 0.528 | 0.5232 |
| 0.2696 | 5.0 | 8125 | 3.0878 | 0.552 | 0.5529 |
| 0.1722 | 6.0 | 9750 | 3.1261 | 0.564 | 0.5608 |
| 0.1138 | 7.0 | 11375 | 3.4324 | 0.576 | 0.5769 |
| 0.0814 | 8.0 | 13000 | 3.6260 | 0.578 | 0.5785 |
| 0.058 | 9.0 | 14625 | 3.7507 | 0.564 | 0.5628 |
| 0.0337 | 10.0 | 16250 | 3.7507 | 0.564 | 0.5646 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1