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README.md
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---
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license: apache-2.0
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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: distilbert-base-uncased__subj__train-8-9
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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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# distilbert-base-uncased__subj__train-8-9
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4865
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- Accuracy: 0.778
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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: 4
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- eval_batch_size: 4
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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: 50
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- mixed_precision_training: Native AMP
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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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| 0.7024 | 1.0 | 3 | 0.6843 | 0.75 |
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| 0.67 | 2.0 | 6 | 0.6807 | 0.5 |
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| 0.6371 | 3.0 | 9 | 0.6677 | 0.5 |
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| 0.585 | 4.0 | 12 | 0.6649 | 0.5 |
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| 0.5122 | 5.0 | 15 | 0.6707 | 0.5 |
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| 0.4379 | 6.0 | 18 | 0.6660 | 0.5 |
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| 0.4035 | 7.0 | 21 | 0.6666 | 0.5 |
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| 0.323 | 8.0 | 24 | 0.6672 | 0.5 |
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| 0.2841 | 9.0 | 27 | 0.6534 | 0.5 |
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| 0.21 | 10.0 | 30 | 0.6456 | 0.5 |
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| 0.1735 | 11.0 | 33 | 0.6325 | 0.5 |
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| 0.133 | 12.0 | 36 | 0.6214 | 0.5 |
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| 0.0986 | 13.0 | 39 | 0.6351 | 0.5 |
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| 0.081 | 14.0 | 42 | 0.6495 | 0.5 |
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| 0.0638 | 15.0 | 45 | 0.6671 | 0.5 |
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| 0.0449 | 16.0 | 48 | 0.7156 | 0.5 |
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| 0.0399 | 17.0 | 51 | 0.7608 | 0.5 |
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| 0.0314 | 18.0 | 54 | 0.7796 | 0.5 |
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| 0.0243 | 19.0 | 57 | 0.7789 | 0.5 |
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| 0.0227 | 20.0 | 60 | 0.7684 | 0.5 |
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| 0.0221 | 21.0 | 63 | 0.7628 | 0.5 |
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| 0.0192 | 22.0 | 66 | 0.7728 | 0.5 |
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### Framework versions
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- Transformers 4.15.0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2
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- Tokenizers 0.10.3
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