library_name: transformers
license: apache-2.0
base_model: bert-base-chinese
tags:
question-answering
generated_from_trainer
metrics: '{"exact": 58.711182388103225, "f1": 58.7488457987073, "total": 6859, "HasAns_exact":
34.578402366863905, "HasAns_f1": 34.67393984220908, "HasAns_total": 2704, "NoAns_exact":
74.41636582430806, "NoAns_f1": 74.41636582430806, "NoAns_total": 4155, "best_exact":
63.58069689459105, "best_exact_thresh": 8.853434701450169e-05, "best_f1": 63.59284638188268,
"best_f1_thresh": 8.853434701450169e-05}'
model-index:
name: rag-qa-base-bert
results: []
rag-qa-base-bert
This model is a fine-tuned version of bert-base-chinese on an unknown dataset.
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: 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
Transformers 4.57.3
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2
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