---
license: mit
base_model: Supabase/gte-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: v_best_model
  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. -->

# v_best_model

This model is a fine-tuned version of [Supabase/gte-small](https://huggingface.co/Supabase/gte-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2700
- Accuracy: 0.9437

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.639         | 1.0   | 21   | 1.3351          | 0.7606   |
| 1.065         | 2.0   | 42   | 0.7793          | 0.8592   |
| 0.6055        | 3.0   | 63   | 0.5200          | 0.8873   |
| 0.3519        | 4.0   | 84   | 0.3832          | 0.9014   |
| 0.2186        | 5.0   | 105  | 0.3277          | 0.9155   |
| 0.1573        | 6.0   | 126  | 0.2844          | 0.9296   |
| 0.118         | 7.0   | 147  | 0.3185          | 0.9014   |
| 0.0948        | 8.0   | 168  | 0.2744          | 0.9437   |
| 0.0831        | 9.0   | 189  | 0.2746          | 0.9437   |
| 0.0778        | 10.0  | 210  | 0.2700          | 0.9437   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0