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---
base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
tags:
- generated_from_trainer
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
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