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--- |
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base_model: klue/roberta-large |
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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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- f1 |
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model-index: |
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- name: pogny-64-0.000001 |
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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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# pogny-64-0.000001 |
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This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2381 |
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- Accuracy: 0.7685 |
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- F1: 0.7667 |
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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: 1e-06 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.0912 | 1.0 | 1205 | 1.2147 | 0.7687 | 0.7677 | |
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| 0.0828 | 2.0 | 2410 | 1.2212 | 0.7681 | 0.7667 | |
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| 0.0787 | 3.0 | 3615 | 1.2381 | 0.7685 | 0.7667 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0a0+b5021ba |
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- Datasets 2.6.2 |
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- Tokenizers 0.14.1 |
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