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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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: finetuned_bert_sentiment_classification |
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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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# finetuned_bert_sentiment_classification |
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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: 1.9785 |
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- Accuracy: 0.78 |
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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: 5e-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: 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 | 68 | 0.6297 | 0.73 | |
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| No log | 2.0 | 136 | 0.9044 | 0.73 | |
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| No log | 3.0 | 204 | 1.2008 | 0.78 | |
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| No log | 4.0 | 272 | 1.4143 | 0.75 | |
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| No log | 5.0 | 340 | 1.4934 | 0.76 | |
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| No log | 6.0 | 408 | 1.5581 | 0.765 | |
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| No log | 7.0 | 476 | 1.6158 | 0.78 | |
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| 0.1371 | 8.0 | 544 | 1.6786 | 0.785 | |
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| 0.1371 | 9.0 | 612 | 1.7112 | 0.78 | |
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| 0.1371 | 10.0 | 680 | 1.7416 | 0.78 | |
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| 0.1371 | 11.0 | 748 | 1.7667 | 0.78 | |
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| 0.1371 | 12.0 | 816 | 1.7937 | 0.78 | |
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| 0.1371 | 13.0 | 884 | 1.8139 | 0.78 | |
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| 0.1371 | 14.0 | 952 | 1.8347 | 0.78 | |
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| 0.0002 | 15.0 | 1020 | 1.8531 | 0.785 | |
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| 0.0002 | 16.0 | 1088 | 1.8645 | 0.78 | |
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| 0.0002 | 17.0 | 1156 | 1.8798 | 0.78 | |
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| 0.0002 | 18.0 | 1224 | 1.8964 | 0.78 | |
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| 0.0002 | 19.0 | 1292 | 1.9097 | 0.78 | |
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| 0.0002 | 20.0 | 1360 | 1.9206 | 0.78 | |
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| 0.0002 | 21.0 | 1428 | 1.9310 | 0.78 | |
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| 0.0002 | 22.0 | 1496 | 1.9410 | 0.78 | |
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| 0.0001 | 23.0 | 1564 | 1.9494 | 0.78 | |
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| 0.0001 | 24.0 | 1632 | 1.9566 | 0.78 | |
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| 0.0001 | 25.0 | 1700 | 1.9628 | 0.78 | |
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| 0.0001 | 26.0 | 1768 | 1.9681 | 0.78 | |
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| 0.0001 | 27.0 | 1836 | 1.9730 | 0.78 | |
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| 0.0001 | 28.0 | 1904 | 1.9761 | 0.78 | |
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| 0.0001 | 29.0 | 1972 | 1.9779 | 0.78 | |
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| 0.0 | 30.0 | 2040 | 1.9785 | 0.78 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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