transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:yelp_polarity base_model:sentence-transformers/all-MiniLM-L6-v2 base_model:finetune:sentence-transformers/all-MiniLM-L6-v2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: sentence-transformers/all-MiniLM-L6-v2
datasets:
- yelp_polarity
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: sbert_yelp2class_fast
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: yelp_polarity
      type: yelp_polarity
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.9733421052631579
      name: Accuracy
---

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# 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
