metadata
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
bert-base-chinese-finetuned-fdRE
This model is a fine-tuned version of 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