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---
license: apache-2.0
base_model: sentence-transformers/all-MiniLM-L6-v2
tags:
- generated_from_trainer
datasets:
- yelp_polarity
metrics:
- accuracy
model-index:
- name: sbert_yelp2class_fast
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yelp_polarity
type: yelp_polarity
config: plain_text
split: test
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.9733421052631579
---
<!-- 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. -->
# sbert_yelp2class_fast
This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on the yelp_polarity dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0831
- Accuracy: 0.9733
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0915 | 1.0 | 17500 | 0.0855 | 0.9710 |
| 0.0676 | 2.0 | 35000 | 0.0831 | 0.9733 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|