---
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: 3.6836
- Accuracy: 0.5091
- Precision: 0.5091
- Recall: 0.5091
- F1: 0.5091

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.3001        | 1.0   | 712   | 1.9740          | 0.4306   | 0.4306    | 0.4306 | 0.4306 |
| 2.0028        | 2.0   | 1424  | 1.9084          | 0.4418   | 0.4418    | 0.4418 | 0.4418 |
| 1.7335        | 3.0   | 2136  | 1.8073          | 0.4642   | 0.4642    | 0.4642 | 0.4642 |
| 1.6116        | 4.0   | 2848  | 1.8696          | 0.4853   | 0.4853    | 0.4853 | 0.4853 |
| 1.2663        | 5.0   | 3560  | 1.8992          | 0.4783   | 0.4783    | 0.4783 | 0.4783 |
| 1.0998        | 6.0   | 4272  | 2.0148          | 0.4923   | 0.4923    | 0.4923 | 0.4923 |
| 1.0126        | 7.0   | 4984  | 2.3935          | 0.4684   | 0.4684    | 0.4684 | 0.4684 |
| 0.7917        | 8.0   | 5696  | 2.5295          | 0.5035   | 0.5035    | 0.5035 | 0.5035 |
| 0.7038        | 9.0   | 6408  | 2.9043          | 0.4909   | 0.4909    | 0.4909 | 0.4909 |
| 0.601         | 10.0  | 7120  | 2.9520          | 0.5021   | 0.5021    | 0.5021 | 0.5021 |
| 0.5927        | 11.0  | 7832  | 3.0934          | 0.5175   | 0.5175    | 0.5175 | 0.5175 |
| 0.5112        | 12.0  | 8544  | 3.2217          | 0.5021   | 0.5021    | 0.5021 | 0.5021 |
| 0.4325        | 13.0  | 9256  | 3.3412          | 0.5119   | 0.5119    | 0.5119 | 0.5119 |
| 0.4005        | 14.0  | 9968  | 3.4485          | 0.5161   | 0.5161    | 0.5161 | 0.5161 |
| 0.3646        | 15.0  | 10680 | 3.6021          | 0.4825   | 0.4825    | 0.4825 | 0.4825 |
| 0.3385        | 16.0  | 11392 | 3.4522          | 0.5203   | 0.5203    | 0.5203 | 0.5203 |
| 0.316         | 17.0  | 12104 | 3.5701          | 0.5175   | 0.5175    | 0.5175 | 0.5175 |
| 0.266         | 18.0  | 12816 | 3.6202          | 0.5063   | 0.5063    | 0.5063 | 0.5063 |
| 0.2518        | 19.0  | 13528 | 3.6250          | 0.5175   | 0.5175    | 0.5175 | 0.5175 |
| 0.254         | 20.0  | 14240 | 3.6836          | 0.5091   | 0.5091    | 0.5091 | 0.5091 |


### Framework versions

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