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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: dream_classifier
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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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# dream_classifier
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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: 1.3533
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- Accuracy: 0.7321
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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: 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: 20
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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 | 17 | 0.5774 | 0.7321 |
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| No log | 2.0 | 34 | 0.5660 | 0.7321 |
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| No log | 3.0 | 51 | 0.5903 | 0.7321 |
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| No log | 4.0 | 68 | 0.5558 | 0.7321 |
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| No log | 5.0 | 85 | 0.5904 | 0.7411 |
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| No log | 6.0 | 102 | 0.6088 | 0.7321 |
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| No log | 7.0 | 119 | 0.7359 | 0.7589 |
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| No log | 8.0 | 136 | 0.9027 | 0.7589 |
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| No log | 9.0 | 153 | 1.0194 | 0.7411 |
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| No log | 10.0 | 170 | 1.1241 | 0.7589 |
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| No log | 11.0 | 187 | 1.1849 | 0.7411 |
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| No log | 12.0 | 204 | 1.2305 | 0.7411 |
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| No log | 13.0 | 221 | 1.2551 | 0.75 |
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| No log | 14.0 | 238 | 1.2859 | 0.7411 |
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| No log | 15.0 | 255 | 1.3070 | 0.7411 |
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| No log | 16.0 | 272 | 1.3238 | 0.7411 |
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| No log | 17.0 | 289 | 1.3357 | 0.7411 |
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| No log | 18.0 | 306 | 1.3449 | 0.7411 |
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| No log | 19.0 | 323 | 1.3513 | 0.7321 |
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| No log | 20.0 | 340 | 1.3533 | 0.7321 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.0
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- Tokenizers 0.13.3
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