---
license: mit
base_model: thenlper/gte-base-zh
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: gte-base-zh-finetuned-emotion
  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. -->

# gte-base-zh-finetuned-emotion

This model is a fine-tuned version of [thenlper/gte-base-zh](https://huggingface.co/thenlper/gte-base-zh) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3958
- Accuracy: 0.8272
- F1: 0.8189

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4103        | 1.0   | 570  | 0.3675          | 0.8333   | 0.8271 |
| 0.3452        | 2.0   | 1140 | 0.3796          | 0.8290   | 0.8180 |
| 0.2784        | 3.0   | 1710 | 0.3930          | 0.8397   | 0.8346 |
| 0.1904        | 4.0   | 2280 | 0.5113          | 0.8364   | 0.8301 |
| 0.1239        | 5.0   | 2850 | 0.6590          | 0.8232   | 0.8100 |
| 0.0828        | 6.0   | 3420 | 0.8153          | 0.8254   | 0.8241 |
| 0.0624        | 7.0   | 3990 | 0.8672          | 0.8250   | 0.8210 |
| 0.0413        | 8.0   | 4560 | 0.9244          | 0.8255   | 0.8159 |
| 0.0303        | 9.0   | 5130 | 1.0888          | 0.8199   | 0.8068 |
| 0.0233        | 10.0  | 5700 | 1.1171          | 0.8250   | 0.8194 |
| 0.0159        | 11.0  | 6270 | 1.2642          | 0.8241   | 0.8115 |
| 0.009         | 12.0  | 6840 | 1.2930          | 0.8265   | 0.8169 |
| 0.0056        | 13.0  | 7410 | 1.3720          | 0.8260   | 0.8150 |
| 0.0019        | 14.0  | 7980 | 1.3878          | 0.8255   | 0.8168 |
| 0.003         | 15.0  | 8550 | 1.3958          | 0.8272   | 0.8189 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2