---
library_name: transformers
license: apache-2.0
base_model: sentence-transformers/all-MiniLM-L6-v2
tags:
- regression
- generated_from_trainer
model-index:
- name: stsb-all-MiniLM-L6-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# stsb-all-MiniLM-L6-v2

This model is a fine-tuned version of sentence-transformers/all-MiniLM-L6-v2 on the Semantic Textual Similarity Benchmark (STS-B) dataset.

It achieves the following results on the evaluation set:
- Loss: 0.0307
- Pearson: 0.8287

## Model description

This model is fine-tuned from the pre-trained sentence-transformers/all-MiniLM-L6-v2 on the Semantic Textual Similarity Benchmark (STS-B) dataset. It is designed to compute similarity scores between pairs of sentences, returning a continuous score between 0 and 1, where 1 represents maximum semantic similarity.

The model generates embeddings for input sentences and can be used for tasks such as text similarity, sentence clustering, or semantic search.


## Training and evaluation data

The model was trained on the STS-B dataset using the following splits:

Train set: 5,749 examples
Validation set: 1,500 examples
Test set: 1,379 examples
Each example consists of two sentences and a similarity score (from 0 to 1) indicating their semantic closeness.


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 360  | 0.0354          | 0.7935  |
| 0.0483        | 2.0   | 720  | 0.0391          | 0.8124  |
| 0.021         | 3.0   | 1080 | 0.0332          | 0.8206  |
| 0.021         | 4.0   | 1440 | 0.0296          | 0.8296  |
| 0.0155        | 5.0   | 1800 | 0.0307          | 0.8287  |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0