End of training

README.md

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+---
+base_model: bert-base-chinese
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: BERT_test_graident_accumulation_test3
+  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. -->
+
+# BERT_test_graident_accumulation_test3
+
+This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1248
+- Accuracy: 0.6072
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 94   | 0.9586          | 0.5826   |
+| No log        | 2.0   | 188  | 0.9446          | 0.6193   |
+| No log        | 3.0   | 282  | 1.0621          | 0.6138   |
+| No log        | 4.0   | 376  | 1.1248          | 0.6072   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.1.1+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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