solikang/koelectra-small-v3-nsmc
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- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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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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This model is a fine-tuned version of [monologg/koelectra-small-v3-discriminator](https://huggingface.co/monologg/koelectra-small-v3-discriminator) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 0.
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Accuracy | F1 |
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| No log | 1.0 |
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| No log | 2.0 | 24 | 0.9140 | 0.8729 | 1.2494 | 0.8354 | 0.9140 |
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| No log | 1.0 | 29 | 0.9304 | 0.8969 | 1.1763 | 0.8657 | 0.9304 |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9173913043478261
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- name: F1
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type: f1
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value: 0.8778665089224095
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- name: Precision
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type: precision
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value: 0.8416068052930057
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- name: Recall
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type: recall
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value: 0.9173913043478261
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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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This model is a fine-tuned version of [monologg/koelectra-small-v3-discriminator](https://huggingface.co/monologg/koelectra-small-v3-discriminator) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2609
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- Accuracy: 0.9174
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- F1: 0.8779
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- Precision: 0.8416
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- Recall: 0.9174
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| No log | 1.0 | 29 | 1.2609 | 0.9174 | 0.8779 | 0.8416 | 0.9174 |
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### Framework versions
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model.safetensors
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