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--- |
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license: mit |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: roberta-large-finetuned-ours-DS |
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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-large-finetuned-ours-DS |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8358 |
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- Accuracy: 0.71 |
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- Precision: 0.6611 |
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- Recall: 0.6691 |
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- F1: 0.6570 |
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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-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 43 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.0561 | 0.99 | 99 | 0.8773 | 0.615 | 0.4054 | 0.5584 | 0.4591 | |
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| 0.762 | 1.98 | 198 | 0.6514 | 0.715 | 0.6735 | 0.6672 | 0.6588 | |
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| 0.5661 | 2.97 | 297 | 0.6806 | 0.71 | 0.6764 | 0.6608 | 0.6435 | |
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| 0.3699 | 3.96 | 396 | 0.8358 | 0.71 | 0.6611 | 0.6691 | 0.6570 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.10.1+cu111 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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