End of training
Browse files- README.md +63 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: mit
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base_model: megagonlabs/transformers-ud-japanese-electra-base-discriminator
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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: electra-based-ja-fc-classifier
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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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# electra-based-ja-fc-classifier
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This model is a fine-tuned version of [megagonlabs/transformers-ud-japanese-electra-base-discriminator](https://huggingface.co/megagonlabs/transformers-ud-japanese-electra-base-discriminator) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1861
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- Accuracy: 0.9414
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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: 3.38340974405913e-05
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- train_batch_size: 16
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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: 3
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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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| 0.3593 | 1.0 | 1223 | 0.2104 | 0.9160 |
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| 0.2137 | 2.0 | 2446 | 0.1861 | 0.9414 |
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| 0.1187 | 3.0 | 3669 | 0.2379 | 0.9355 |
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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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