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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_10_64_0.01 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bella05/huggingface/runs/2fqy4l1d) |
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# pogny_10_64_0.01 |
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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: 1.6851 |
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- Accuracy: 0.4376 |
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- F1: 0.2665 |
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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: 0.01 |
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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: 10 |
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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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| 2.491 | 1.0 | 1205 | 2.5033 | 0.4376 | 0.2665 | |
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| 2.4679 | 2.0 | 2410 | 1.9460 | 0.4376 | 0.2665 | |
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| 2.302 | 3.0 | 3615 | 2.4098 | 0.0702 | 0.0092 | |
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| 2.1762 | 4.0 | 4820 | 2.2698 | 0.0545 | 0.0056 | |
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| 2.0639 | 5.0 | 6025 | 1.9917 | 0.4376 | 0.2665 | |
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| 2.0031 | 6.0 | 7230 | 1.9130 | 0.4376 | 0.2665 | |
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| 1.9241 | 7.0 | 8435 | 2.0131 | 0.4376 | 0.2665 | |
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| 1.8227 | 8.0 | 9640 | 1.8212 | 0.4376 | 0.2665 | |
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| 1.7854 | 9.0 | 10845 | 1.7379 | 0.4376 | 0.2665 | |
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| 1.7037 | 10.0 | 12050 | 1.6851 | 0.4376 | 0.2665 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.2.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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