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--- |
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license: apache-2.0 |
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base_model: knowledgator/comprehend_it-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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model-index: |
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- name: Mongolian_GPT_FakeNews_Comprehendo |
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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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# Mongolian_GPT_FakeNews_Comprehendo |
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This model is a fine-tuned version of [knowledgator/comprehend_it-base](https://huggingface.co/knowledgator/comprehend_it-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3175 |
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- Accuracy: 0.8393 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 3 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.1788 | 1.0 | 11 | 0.7540 | 0.8571 | |
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| 0.2589 | 2.0 | 22 | 0.6399 | 0.8571 | |
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| 0.1117 | 3.0 | 33 | 0.6795 | 0.8125 | |
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| 0.0829 | 4.0 | 44 | 0.6606 | 0.8571 | |
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| 0.0037 | 5.0 | 55 | 0.7375 | 0.8482 | |
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| 0.0017 | 6.0 | 66 | 0.8388 | 0.8393 | |
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| 0.0009 | 7.0 | 77 | 0.8872 | 0.8393 | |
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| 0.0007 | 8.0 | 88 | 0.9371 | 0.8393 | |
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| 0.0005 | 9.0 | 99 | 0.9949 | 0.8393 | |
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| 0.0004 | 10.0 | 110 | 1.0329 | 0.8393 | |
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| 0.0003 | 11.0 | 121 | 1.0626 | 0.8393 | |
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| 0.0003 | 12.0 | 132 | 1.0800 | 0.8393 | |
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| 0.0002 | 13.0 | 143 | 1.0993 | 0.8393 | |
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| 0.0002 | 14.0 | 154 | 1.1330 | 0.8393 | |
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| 0.0002 | 15.0 | 165 | 1.1925 | 0.8393 | |
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| 0.0001 | 16.0 | 176 | 1.2286 | 0.8393 | |
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| 0.0001 | 17.0 | 187 | 1.2468 | 0.8393 | |
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| 0.0001 | 18.0 | 198 | 1.2586 | 0.8393 | |
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| 0.0001 | 19.0 | 209 | 1.2686 | 0.8393 | |
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| 0.0001 | 20.0 | 220 | 1.2758 | 0.8393 | |
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| 0.0001 | 21.0 | 231 | 1.2836 | 0.8393 | |
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| 0.0001 | 22.0 | 242 | 1.2914 | 0.8393 | |
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| 0.0001 | 23.0 | 253 | 1.2978 | 0.8393 | |
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| 0.0001 | 24.0 | 264 | 1.3027 | 0.8393 | |
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| 0.0001 | 25.0 | 275 | 1.3070 | 0.8393 | |
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| 0.0001 | 26.0 | 286 | 1.3106 | 0.8393 | |
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| 0.0001 | 27.0 | 297 | 1.3131 | 0.8393 | |
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| 0.0001 | 28.0 | 308 | 1.3156 | 0.8393 | |
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| 0.0001 | 29.0 | 319 | 1.3170 | 0.8393 | |
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| 0.0001 | 30.0 | 330 | 1.3175 | 0.8393 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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