Model save
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README.md
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---
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base_model: Kevinger/setfit-hub-report
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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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- accuracy
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model-index:
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- name: Hub-Repoop-1706130115
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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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# Hub-Repoop-1706130115
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This model is a fine-tuned version of [Kevinger/setfit-hub-report](https://huggingface.co/Kevinger/setfit-hub-report) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1746
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- F1: 0.7727
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- Roc Auc: 0.8666
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- Accuracy: 0.7637
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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: 8
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- eval_batch_size: 8
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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: 13
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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| No log | 1.0 | 277 | 0.3104 | 0.0 | 0.5 | 0.0 |
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| 0.3599 | 2.0 | 554 | 0.2312 | 0.5624 | 0.7027 | 0.4135 |
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| 0.3599 | 3.0 | 831 | 0.1897 | 0.7479 | 0.8275 | 0.6730 |
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| 0.2035 | 4.0 | 1108 | 0.1768 | 0.7645 | 0.8546 | 0.7363 |
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| 0.2035 | 5.0 | 1385 | 0.1760 | 0.7649 | 0.8579 | 0.7447 |
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| 0.1422 | 6.0 | 1662 | 0.1788 | 0.7559 | 0.8562 | 0.7447 |
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| 0.1422 | 7.0 | 1939 | 0.1766 | 0.7633 | 0.8617 | 0.7553 |
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| 0.1096 | 8.0 | 2216 | 0.1746 | 0.7727 | 0.8666 | 0.7637 |
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| 0.1096 | 9.0 | 2493 | 0.1891 | 0.7457 | 0.8511 | 0.7363 |
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| 0.0891 | 10.0 | 2770 | 0.1855 | 0.7524 | 0.8540 | 0.7405 |
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| 0.0769 | 11.0 | 3047 | 0.1824 | 0.7655 | 0.8629 | 0.7574 |
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| 0.0769 | 12.0 | 3324 | 0.1835 | 0.7655 | 0.8629 | 0.7532 |
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| 0.0706 | 13.0 | 3601 | 0.1867 | 0.7604 | 0.8603 | 0.7511 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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model.safetensors
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runs/Jan24_21-02-28_fa6cdd9e7bef/events.out.tfevents.1706130732.fa6cdd9e7bef.2645.1
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tokenizer.json
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