---
tags:
- generated_from_trainer
base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: all_keywords_multi-qa-MiniLM-L6-cos-v1_another
  results: []
---

<!-- 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. -->

# all_keywords_multi-qa-MiniLM-L6-cos-v1_another

This model is a fine-tuned version of [sentence-transformers/multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7780
- Accuracy: 0.5526
- Precision: 0.5526
- Recall: 0.5526
- F1: 0.5526

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.3017        | 1.0   | 712   | 2.0180          | 0.4362   |
| 2.09          | 2.0   | 1424  | 1.8306          | 0.4390   |
| 1.775         | 3.0   | 2136  | 1.7843          | 0.4783   |
| 1.5811        | 4.0   | 2848  | 1.7686          | 0.5175   |
| 1.2665        | 5.0   | 3560  | 1.7257          | 0.5147   |
| 1.0957        | 6.0   | 4272  | 1.8126          | 0.5568   |
| 0.9661        | 7.0   | 4984  | 2.0472          | 0.5386   |
| 0.7399        | 8.0   | 5696  | 2.1375          | 0.5428   |
| 0.6533        | 9.0   | 6408  | 2.2761          | 0.5400   |
| 0.5268        | 10.0  | 7120  | 2.4777          | 0.5400   |
| 0.5067        | 11.0  | 7832  | 2.6160          | 0.5372   |
| 0.4209        | 12.0  | 8544  | 2.6253          | 0.5512   |
| 0.4102        | 13.0  | 9256  | 2.7287          | 0.5442   |
| 0.3405        | 14.0  | 9968  | 2.7607          | 0.5470   |
| 0.3278        | 15.0  | 10680 | 2.7780          | 0.5526   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu118
- Datasets 2.14.7
- Tokenizers 0.15.2