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---
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
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