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---
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
---
<!-- 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. -->
# 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
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