metadata
library_name: peft
license: apache-2.0
base_model: bert-base-chinese
tags:
- base_model:adapter:bert-base-chinese
- lora
- transformers
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-chinese-sentiment
results: []
bert-chinese-sentiment
This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7466
- Accuracy: 0.5
- F1: 0.0
- Precision: 0.0
- Recall: 0.0
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.17.1
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0