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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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- f1 |
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model-index: |
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- name: source-type-model |
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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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# source-type-model |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6271 |
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- F1: 0.6772 |
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Classifies the following tags: |
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``` |
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'Cannot Determine' |
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'Report/Document' |
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'Named Individual' |
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'Unnamed Individual' |
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'Database' |
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'Unnamed Group' |
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'Named Group' |
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'Vote/Poll' |
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``` |
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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: 5e-05 |
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- train_batch_size: 5 |
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- eval_batch_size: 5 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 0.12 | 100 | 0.7192 | 0.3792 | |
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| No log | 0.25 | 200 | 0.7716 | 0.4005 | |
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| No log | 0.37 | 300 | 0.7565 | 0.5297 | |
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| No log | 0.49 | 400 | 0.5788 | 0.5806 | |
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| 0.8223 | 0.62 | 500 | 0.5402 | 0.5933 | |
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| 0.8223 | 0.74 | 600 | 0.5032 | 0.6666 | |
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| 0.8223 | 0.86 | 700 | 0.4658 | 0.6754 | |
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| 0.8223 | 0.99 | 800 | 0.5359 | 0.6441 | |
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| 0.8223 | 1.11 | 900 | 0.5295 | 0.6442 | |
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| 0.6009 | 1.23 | 1000 | 0.6077 | 0.6597 | |
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| 0.6009 | 1.35 | 1100 | 0.6169 | 0.6360 | |
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| 0.6009 | 1.48 | 1200 | 0.6014 | 0.6277 | |
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| 0.6009 | 1.6 | 1300 | 0.6382 | 0.6327 | |
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| 0.6009 | 1.72 | 1400 | 0.5226 | 0.6787 | |
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| 0.5644 | 1.85 | 1500 | 0.4922 | 0.6485 | |
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| 0.5644 | 1.97 | 1600 | 0.6181 | 0.6517 | |
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| 0.5644 | 2.09 | 1700 | 0.6106 | 0.6781 | |
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| 0.5644 | 2.22 | 1800 | 0.6652 | 0.6760 | |
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| 0.5644 | 2.34 | 1900 | 0.6252 | 0.6739 | |
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| 0.3299 | 2.46 | 2000 | 0.6620 | 0.6606 | |
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| 0.3299 | 2.59 | 2100 | 0.6317 | 0.6772 | |
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| 0.3299 | 2.71 | 2200 | 0.6170 | 0.6726 | |
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| 0.3299 | 2.83 | 2300 | 0.6400 | 0.6773 | |
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| 0.3299 | 2.96 | 2400 | 0.6271 | 0.6772 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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