---
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: 3.2408
- Accuracy: 0.5259
- Precision: 0.5259
- Recall: 0.5259
- F1: 0.5259

## 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.3237        | 1.0   | 712   | 1.9365          | 0.4123   | 0.4123    | 0.4123 | 0.4123 |
| 2.0274        | 2.0   | 1424  | 1.8781          | 0.4502   | 0.4502    | 0.4502 | 0.4502 |
| 1.7498        | 3.0   | 2136  | 1.7664          | 0.4656   | 0.4656    | 0.4656 | 0.4656 |
| 1.6009        | 4.0   | 2848  | 1.7801          | 0.4656   | 0.4656    | 0.4656 | 0.4656 |
| 1.2981        | 5.0   | 3560  | 1.9004          | 0.4600   | 0.4600    | 0.4600 | 0.4600 |
| 1.0895        | 6.0   | 4272  | 2.0621          | 0.4642   | 0.4642    | 0.4642 | 0.4642 |
| 0.9878        | 7.0   | 4984  | 2.4640          | 0.4572   | 0.4572    | 0.4572 | 0.4572 |
| 0.784         | 8.0   | 5696  | 2.5635          | 0.5091   | 0.5091    | 0.5091 | 0.5091 |
| 0.6569        | 9.0   | 6408  | 2.5690          | 0.5273   | 0.5273    | 0.5273 | 0.5273 |
| 0.5847        | 10.0  | 7120  | 2.9342          | 0.5063   | 0.5063    | 0.5063 | 0.5063 |
| 0.5107        | 11.0  | 7832  | 2.9652          | 0.5091   | 0.5091    | 0.5091 | 0.5091 |
| 0.4954        | 12.0  | 8544  | 3.1480          | 0.5161   | 0.5161    | 0.5161 | 0.5161 |
| 0.4274        | 13.0  | 9256  | 3.2199          | 0.4993   | 0.4993    | 0.4993 | 0.4993 |
| 0.433         | 14.0  | 9968  | 3.2185          | 0.5217   | 0.5217    | 0.5217 | 0.5217 |
| 0.3615        | 15.0  | 10680 | 3.2408          | 0.5259   | 0.5259    | 0.5259 | 0.5259 |


### Framework versions

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