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---
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
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