---
base_model: nghuyong/ernie-2.0-base-en
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ernie-2.0-base-en
  results: []
---

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# ernie-2.0-base-en

This model is a fine-tuned version of [nghuyong/ernie-2.0-base-en](https://huggingface.co/nghuyong/ernie-2.0-base-en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2022
- Precision: 0.7745
- Recall: 0.8255
- F1: 0.7992
- Accuracy: 0.9392

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2221        | 1.0   | 2078 | 0.2066          | 0.7130    | 0.8024 | 0.7551 | 0.9309   |
| 0.1813        | 2.0   | 4156 | 0.1972          | 0.7573    | 0.8224 | 0.7885 | 0.9362   |
| 0.1397        | 3.0   | 6234 | 0.2022          | 0.7745    | 0.8255 | 0.7992 | 0.9392   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1