---
license: cc-by-nc-4.0
pipeline_tag: sentence-similarity
tags:
    - sentence-transformers
    - feature-extraction
    - sentence-similarity
    - transformers
    - generated_from_trainer
datasets:
    - squad
    - newsqa
    - LLukas22/cqadupstack
    - LLukas22/fiqa
    - LLukas22/scidocs
    - deepset/germanquad
    - LLukas22/nq
---

# all-MiniLM-L12-v2-embedding-all

This model is a fine-tuned version of [all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) on the following datasets: [squad](https://huggingface.co/datasets/squad), [newsqa](https://huggingface.co/datasets/newsqa), [LLukas22/cqadupstack](https://huggingface.co/datasets/LLukas22/cqadupstack), [LLukas22/fiqa](https://huggingface.co/datasets/LLukas22/fiqa), [LLukas22/scidocs](https://huggingface.co/datasets/LLukas22/scidocs), [deepset/germanquad](https://huggingface.co/datasets/deepset/germanquad), [LLukas22/nq](https://huggingface.co/datasets/LLukas22/nq).



## Usage (Sentence-Transformers)

Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('LLukas22/all-MiniLM-L12-v2-embedding-all')
embeddings = model.encode(sentences)
print(embeddings)
```

## Training hyperparameters
The following hyperparameters were used during training:

- learning_rate: 2E-05
- per device batch size: 60
- effective batch size: 120
- seed: 42
- optimizer: AdamW with betas (0.9,0.999) and eps 1E-08
- weight decay: 1E-02
- number of epochs: 4
- mixed_precision_training: bf16

## Training results
| Epoch | Train Loss | Validation Loss |
| ----- | ---------- | --------------- |
| 0 | 0.0655 | 0.055 |
| 1 | 0.0549 | 0.051 |
| 2 | 0.049 | 0.0481 |
| 3 | 0.0451 | 0.0471 |

## Evaluation results
| Epoch | top_1 | top_3 | top_5 | top_10 | top_25 |
| ----- | ----- | ----- | ----- | ----- | ----- |
| 0 | 0.537 | 0.697 | 0.753 | 0.812 | 0.867 |
| 1 | 0.538 | 0.699 | 0.755 | 0.814 | 0.872 |
| 2 | 0.544 | 0.705 | 0.761 | 0.818 | 0.876 |
| 3 | 0.544 | 0.703 | 0.759 | 0.817 | 0.874 |

## Framework versions
- Transformers: 4.25.1
- PyTorch: 1.13.0+cu116
- PyTorch Lightning: 1.8.6
- Datasets: 2.7.1
- Tokenizers: 0.13.1
- Sentence Transformers: 2.2.2

## Additional Information
This model was trained as part of my Master's Thesis **'Evaluation of transformer based language models for use in service information systems'**. The source code is available on [Github](https://github.com/LLukas22/Master).