README.md

---
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
license: mit
language:
- en
- ru
---

# Multilingual E5 WB

Fine-tuned version of default [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) for WB DS School and RAG project.

## Evaluation Results

<!--- Describe how your model was evaluated -->
As model is used as retriever, **goal was to boost its performance at cosine similarity between question and answer.** 
With given dataset of QA pairs model performance on EmbeddingSimilarityEvaluator improved from **0.62 to 0.78.**


## Fine Tuning

**DataLoader**:

`torch.utils.data.dataloader.DataLoader` of length 790 with parameters:
```
{'batch_size': 12, 'sampler': 'torch.utils.data.sampler.SequentialSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
```

**Loss**:

`sentence_transformers.losses.ContrastiveLoss.ContrastiveLoss` with parameters:
  ```
  {'distance_metric': 'SiameseDistanceMetric.COSINE_DISTANCE', 'margin': 0.5, 'size_average': True}
  ```

Parameters of the fit()-Method:
```
{
    "epochs": 10,
    "evaluation_steps": 100,
    "evaluator": "sentence_transformers.evaluation.EmbeddingSimilarityEvaluator.EmbeddingSimilarityEvaluator",
    "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
    "optimizer_params": {
        "lr": 2e-05
    },
    "scheduler": "WarmupLinear",
    "steps_per_epoch": null,
    "warmup_steps": 790,
    "weight_decay": 0.01
}
```