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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- yelp_polarity
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-yelp-polarity
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yelp_polarity
type: yelp_polarity
config: plain_text
split: train
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.9617414248021108
- name: F1
type: f1
value: 0.9617407987866946
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-yelp-polarity
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the yelp_polarity dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1395
- Accuracy: 0.9617
- F1: 0.9617
## 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: 24
- eval_batch_size: 24
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.1334 | 1.0 | 2332 | 0.1141 | 0.9602 | 0.9602 |
| 0.0722 | 2.0 | 4664 | 0.1395 | 0.9617 | 0.9617 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
|