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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_32_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/8upm8cw9) |
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# pogny_10_32_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: 1.6859 |
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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: 32 |
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- eval_batch_size: 32 |
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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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| 2.8512 | 1.0 | 2409 | 3.1877 | 0.4376 | 0.2665 | |
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| 2.7295 | 2.0 | 4818 | 3.5982 | 0.0702 | 0.0092 | |
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| 2.5873 | 3.0 | 7227 | 1.9106 | 0.4376 | 0.2665 | |
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| 2.3248 | 4.0 | 9636 | 2.4274 | 0.4376 | 0.2665 | |
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| 2.2087 | 5.0 | 12045 | 2.0673 | 0.2545 | 0.1032 | |
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| 2.17 | 6.0 | 14454 | 2.3342 | 0.4376 | 0.2665 | |
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| 2.0611 | 7.0 | 16863 | 1.9937 | 0.4376 | 0.2665 | |
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| 1.8834 | 8.0 | 19272 | 1.8107 | 0.4376 | 0.2665 | |
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| 1.7959 | 9.0 | 21681 | 1.7571 | 0.4376 | 0.2665 | |
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| 1.7009 | 10.0 | 24090 | 1.6859 | 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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