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--- |
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base_model: klue/roberta-base |
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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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- precision |
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- recall |
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model-index: |
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- name: roberta-base-finetuned-tc |
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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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# roberta-base-finetuned-tc |
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This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5805 |
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- Accuracy: 0.8378 |
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- F1: 0.8303 |
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- Precision: 0.8386 |
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- Recall: 0.8378 |
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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: 2e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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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- lr_scheduler_warmup_steps: 10 |
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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 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 13 | 1.4532 | 0.4777 | 0.3088 | 0.2282 | 0.4777 | |
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| No log | 2.0 | 26 | 1.1224 | 0.6190 | 0.5210 | 0.4641 | 0.6190 | |
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| No log | 3.0 | 39 | 0.8175 | 0.7560 | 0.7238 | 0.7040 | 0.7560 | |
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| No log | 4.0 | 52 | 0.7069 | 0.7932 | 0.7712 | 0.7526 | 0.7932 | |
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| No log | 5.0 | 65 | 0.6515 | 0.8110 | 0.7895 | 0.7705 | 0.8110 | |
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| No log | 6.0 | 78 | 0.6212 | 0.8170 | 0.7983 | 0.8023 | 0.8170 | |
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| No log | 7.0 | 91 | 0.6025 | 0.8304 | 0.8163 | 0.8395 | 0.8304 | |
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| No log | 8.0 | 104 | 0.5982 | 0.8318 | 0.8238 | 0.8330 | 0.8318 | |
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| No log | 9.0 | 117 | 0.5815 | 0.8348 | 0.8260 | 0.8344 | 0.8348 | |
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| No log | 10.0 | 130 | 0.5805 | 0.8378 | 0.8303 | 0.8386 | 0.8378 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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