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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__sst2__train-16-3
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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__sst2__train-16-3
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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: 0.7887
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- Accuracy: 0.6458
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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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| 0.6928 | 1.0 | 7 | 0.6973 | 0.4286 |
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| 0.675 | 2.0 | 14 | 0.7001 | 0.4286 |
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| 0.6513 | 3.0 | 21 | 0.6959 | 0.4286 |
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| 0.5702 | 4.0 | 28 | 0.6993 | 0.4286 |
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| 0.5389 | 5.0 | 35 | 0.6020 | 0.7143 |
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| 0.3386 | 6.0 | 42 | 0.5326 | 0.5714 |
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| 0.2596 | 7.0 | 49 | 0.4943 | 0.7143 |
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| 0.1633 | 8.0 | 56 | 0.3589 | 0.8571 |
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| 0.1086 | 9.0 | 63 | 0.2924 | 0.8571 |
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| 0.0641 | 10.0 | 70 | 0.2687 | 0.8571 |
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| 0.0409 | 11.0 | 77 | 0.2202 | 0.8571 |
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| 0.0181 | 12.0 | 84 | 0.2445 | 0.8571 |
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| 0.0141 | 13.0 | 91 | 0.2885 | 0.8571 |
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| 0.0108 | 14.0 | 98 | 0.3069 | 0.8571 |
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| 0.009 | 15.0 | 105 | 0.3006 | 0.8571 |
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| 0.0084 | 16.0 | 112 | 0.2834 | 0.8571 |
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| 0.0088 | 17.0 | 119 | 0.2736 | 0.8571 |
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| 0.0062 | 18.0 | 126 | 0.2579 | 0.8571 |
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| 0.0058 | 19.0 | 133 | 0.2609 | 0.8571 |
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| 0.0057 | 20.0 | 140 | 0.2563 | 0.8571 |
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| 0.0049 | 21.0 | 147 | 0.2582 | 0.8571 |
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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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