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--- |
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license: apache-2.0 |
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base_model: line-corporation/line-distilbert-base-japanese |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: factual-consistency-classification-ja-avgpool |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# factual-consistency-classification-ja-avgpool |
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This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4881 |
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- Accuracy: 0.8223 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: tpu |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 306 | 0.6837 | 0.7402 | |
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| 0.7763 | 2.0 | 612 | 0.6102 | 0.7734 | |
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| 0.7763 | 3.0 | 918 | 0.5782 | 0.7832 | |
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| 0.657 | 4.0 | 1224 | 0.5698 | 0.7949 | |
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| 0.6267 | 5.0 | 1530 | 0.5743 | 0.7793 | |
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| 0.6267 | 6.0 | 1836 | 0.5465 | 0.8066 | |
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| 0.6082 | 7.0 | 2142 | 0.5474 | 0.8066 | |
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| 0.6082 | 8.0 | 2448 | 0.5488 | 0.7949 | |
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| 0.5976 | 9.0 | 2754 | 0.5359 | 0.8125 | |
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| 0.5845 | 10.0 | 3060 | 0.5236 | 0.8086 | |
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| 0.5845 | 11.0 | 3366 | 0.5240 | 0.8027 | |
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| 0.5769 | 12.0 | 3672 | 0.5120 | 0.8125 | |
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| 0.5769 | 13.0 | 3978 | 0.5105 | 0.8125 | |
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| 0.5742 | 14.0 | 4284 | 0.5282 | 0.7969 | |
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| 0.5631 | 15.0 | 4590 | 0.5026 | 0.8086 | |
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| 0.5631 | 16.0 | 4896 | 0.5120 | 0.8125 | |
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| 0.5529 | 17.0 | 5202 | 0.4996 | 0.8145 | |
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| 0.5525 | 18.0 | 5508 | 0.4928 | 0.8145 | |
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| 0.5525 | 19.0 | 5814 | 0.5143 | 0.8027 | |
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| 0.5471 | 20.0 | 6120 | 0.4859 | 0.8203 | |
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| 0.5471 | 21.0 | 6426 | 0.4923 | 0.8145 | |
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| 0.5397 | 22.0 | 6732 | 0.4874 | 0.8242 | |
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| 0.5404 | 23.0 | 7038 | 0.4926 | 0.8184 | |
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| 0.5404 | 24.0 | 7344 | 0.4913 | 0.8223 | |
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| 0.5375 | 25.0 | 7650 | 0.4914 | 0.8223 | |
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| 0.5375 | 26.0 | 7956 | 0.4960 | 0.8047 | |
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| 0.5301 | 27.0 | 8262 | 0.4883 | 0.8203 | |
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| 0.5313 | 28.0 | 8568 | 0.4890 | 0.8223 | |
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| 0.5313 | 29.0 | 8874 | 0.4918 | 0.8203 | |
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| 0.5318 | 30.0 | 9180 | 0.4881 | 0.8223 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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