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BERT_test_graident_accumulation_test4
BrianHsu/BERT_test_graident_accumulation_test4
BERT_test_graident_accumulation_test4 is a multiple choice model from BrianHsu. Use it for the multiple choice task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- multiple choice
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Dec 18, 2023
- Updated
- Dec 18, 2023
- SHA
- d1a693ae
Base models
Model card
From the Hugging Face model README
<!-- 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_test4
This model is a fine-tuned version of bert-base-chinese on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1752
- Accuracy: 0.5781
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 116 | 1.0083 | 0.5586 |
| No log | 1.99 | 232 | 1.0274 | 0.5913 |
| No log | 2.99 | 348 | 1.1752 | 0.5781 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- multiple choice
- Library
- transformers
- Type
- bert
- Created
- Dec 18, 2023
- Updated
- Dec 18, 2023