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--- |
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base_model: neal49/distilbert-sst2-runglue |
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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: dnd |
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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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# dnd |
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This model is a fine-tuned version of [neal49/distilbert-sst2-runglue](https://huggingface.co/neal49/distilbert-sst2-runglue) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4907 |
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- Accuracy: 0.8246 |
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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-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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| No log | 1.0 | 15 | 0.6813 | 0.5789 | |
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| No log | 2.0 | 30 | 0.6725 | 0.5789 | |
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| No log | 3.0 | 45 | 0.6588 | 0.6140 | |
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| No log | 4.0 | 60 | 0.6536 | 0.6140 | |
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| No log | 5.0 | 75 | 0.6524 | 0.6140 | |
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| No log | 6.0 | 90 | 0.6426 | 0.6140 | |
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| No log | 7.0 | 105 | 0.6333 | 0.6316 | |
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| No log | 8.0 | 120 | 0.6148 | 0.6491 | |
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| No log | 9.0 | 135 | 0.6081 | 0.6491 | |
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| No log | 10.0 | 150 | 0.5724 | 0.7018 | |
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| No log | 11.0 | 165 | 0.5984 | 0.6842 | |
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| No log | 12.0 | 180 | 0.5328 | 0.7368 | |
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| No log | 13.0 | 195 | 0.5419 | 0.7719 | |
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| No log | 14.0 | 210 | 0.5271 | 0.7719 | |
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| No log | 15.0 | 225 | 0.5188 | 0.7719 | |
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| No log | 16.0 | 240 | 0.5283 | 0.7719 | |
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| No log | 17.0 | 255 | 0.5012 | 0.7719 | |
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| No log | 18.0 | 270 | 0.4863 | 0.7895 | |
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| No log | 19.0 | 285 | 0.5329 | 0.7895 | |
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| No log | 20.0 | 300 | 0.4861 | 0.8070 | |
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| No log | 21.0 | 315 | 0.5065 | 0.8246 | |
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| No log | 22.0 | 330 | 0.4864 | 0.8070 | |
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| No log | 23.0 | 345 | 0.5060 | 0.8246 | |
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| No log | 24.0 | 360 | 0.4752 | 0.8246 | |
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| No log | 25.0 | 375 | 0.4983 | 0.8246 | |
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| No log | 26.0 | 390 | 0.4925 | 0.8246 | |
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| No log | 27.0 | 405 | 0.4774 | 0.8246 | |
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| No log | 28.0 | 420 | 0.4804 | 0.8246 | |
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| No log | 29.0 | 435 | 0.4927 | 0.8246 | |
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| No log | 30.0 | 450 | 0.4907 | 0.8246 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.13.2 |
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