End of training

README.md

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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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