---
license: mit
base_model: thenlper/gte-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Classify-model-v1.2
  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. -->

# Classify-model-v1.2

This model is a fine-tuned version of [thenlper/gte-large](https://huggingface.co/thenlper/gte-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3536
- Accuracy: 0.9107

## 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: 9.5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3025        | 1.0   | 11   | 0.7724          | 0.7411   |
| 0.5536        | 2.0   | 22   | 0.4194          | 0.9018   |
| 0.2468        | 3.0   | 33   | 0.4068          | 0.875    |
| 0.111         | 4.0   | 44   | 0.3455          | 0.8839   |
| 0.0531        | 5.0   | 55   | 0.3453          | 0.8929   |
| 0.0305        | 6.0   | 66   | 0.3536          | 0.9107   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2