LABEL_0 LABEL_1 LABEL_2
---
tags:
- generated_from_trainer
datasets:
- sem_eval2010_task8
metrics:
- accuracy
model-index:
- name: bert-base-chinese-finetuned-fdRE
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: sem_eval2010_task8
      type: sem_eval2010_task8
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9080962800875274
---

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# bert-base-chinese-finetuned-fdRE

This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the sem_eval2010_task8 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2716
- Accuracy: 0.9081

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 46   | 0.5571          | 0.7812   |
| No log        | 2.0   | 92   | 0.4030          | 0.8621   |
| No log        | 3.0   | 138  | 0.3139          | 0.8928   |
| No log        | 4.0   | 184  | 0.2716          | 0.9081   |
| No log        | 5.0   | 230  | 0.2564          | 0.9081   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
