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---
base_model: bert-base-chinese
tags:
- generated_from_trainer
model-index:
- name: ntu_adl_span_selection_bert
results: []
---
<!-- 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. -->
# ntu_adl_span_selection_bert
This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co./bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0552
- Em Accuracy: 0.7607
## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- 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 | Em Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|
| 1.161 | 1.0 | 10857 | 1.2192 | 0.7029 |
| 0.7596 | 2.0 | 21714 | 1.3003 | 0.7338 |
| 0.551 | 3.0 | 32571 | 1.5081 | 0.7398 |
| 0.2034 | 4.0 | 43428 | 1.8194 | 0.7474 |
| 0.0762 | 5.0 | 54285 | 2.0552 | 0.7607 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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