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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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datasets: |
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- sentiment140 |
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metrics: |
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- accuracy |
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model-index: |
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- name: Sentiment140_BERT_5E |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: sentiment140 |
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type: sentiment140 |
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config: sentiment140 |
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split: train |
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args: sentiment140 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.82 |
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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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# Sentiment140_BERT_5E |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the sentiment140 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7061 |
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- Accuracy: 0.82 |
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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: 1e-05 |
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- train_batch_size: 16 |
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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: 5 |
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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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| 0.6882 | 0.08 | 50 | 0.6047 | 0.7 | |
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| 0.6223 | 0.16 | 100 | 0.5137 | 0.8067 | |
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| 0.5463 | 0.24 | 150 | 0.4573 | 0.8067 | |
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| 0.4922 | 0.32 | 200 | 0.4790 | 0.8 | |
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| 0.4821 | 0.4 | 250 | 0.4207 | 0.8267 | |
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| 0.4985 | 0.48 | 300 | 0.4267 | 0.8067 | |
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| 0.4455 | 0.56 | 350 | 0.4301 | 0.8133 | |
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| 0.469 | 0.64 | 400 | 0.4294 | 0.82 | |
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| 0.4906 | 0.72 | 450 | 0.4059 | 0.8067 | |
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| 0.4006 | 0.8 | 500 | 0.4181 | 0.8133 | |
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| 0.445 | 0.88 | 550 | 0.3948 | 0.8267 | |
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| 0.4302 | 0.96 | 600 | 0.3976 | 0.84 | |
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| 0.4442 | 1.04 | 650 | 0.3887 | 0.8533 | |
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| 0.3424 | 1.12 | 700 | 0.4119 | 0.8267 | |
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| 0.3589 | 1.2 | 750 | 0.4083 | 0.8533 | |
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| 0.3737 | 1.28 | 800 | 0.4253 | 0.8333 | |
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| 0.334 | 1.36 | 850 | 0.4147 | 0.86 | |
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| 0.3637 | 1.44 | 900 | 0.3926 | 0.8533 | |
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| 0.3388 | 1.52 | 950 | 0.4084 | 0.8267 | |
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| 0.3375 | 1.6 | 1000 | 0.4132 | 0.8467 | |
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| 0.3725 | 1.68 | 1050 | 0.3965 | 0.8467 | |
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| 0.3649 | 1.76 | 1100 | 0.3956 | 0.8333 | |
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| 0.3799 | 1.84 | 1150 | 0.3923 | 0.8333 | |
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| 0.3695 | 1.92 | 1200 | 0.4266 | 0.84 | |
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| 0.3233 | 2.0 | 1250 | 0.4225 | 0.8333 | |
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| 0.2313 | 2.08 | 1300 | 0.4672 | 0.8333 | |
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| 0.231 | 2.16 | 1350 | 0.5212 | 0.8133 | |
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| 0.2526 | 2.24 | 1400 | 0.5392 | 0.8067 | |
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| 0.2721 | 2.32 | 1450 | 0.4895 | 0.82 | |
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| 0.2141 | 2.4 | 1500 | 0.5258 | 0.8133 | |
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| 0.2658 | 2.48 | 1550 | 0.5046 | 0.8267 | |
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| 0.2386 | 2.56 | 1600 | 0.4873 | 0.8267 | |
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| 0.2493 | 2.64 | 1650 | 0.4950 | 0.8333 | |
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| 0.2692 | 2.72 | 1700 | 0.5080 | 0.8267 | |
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| 0.2226 | 2.8 | 1750 | 0.5016 | 0.8467 | |
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| 0.2522 | 2.88 | 1800 | 0.5068 | 0.8267 | |
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| 0.2556 | 2.96 | 1850 | 0.4937 | 0.8267 | |
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| 0.2311 | 3.04 | 1900 | 0.5103 | 0.8267 | |
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| 0.1703 | 3.12 | 1950 | 0.5680 | 0.82 | |
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| 0.1744 | 3.2 | 2000 | 0.5501 | 0.82 | |
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| 0.1667 | 3.28 | 2050 | 0.6142 | 0.82 | |
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| 0.1863 | 3.36 | 2100 | 0.6355 | 0.82 | |
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| 0.2543 | 3.44 | 2150 | 0.6000 | 0.8133 | |
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| 0.1565 | 3.52 | 2200 | 0.6618 | 0.8267 | |
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| 0.1531 | 3.6 | 2250 | 0.6595 | 0.8133 | |
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| 0.1915 | 3.68 | 2300 | 0.6647 | 0.8267 | |
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| 0.1601 | 3.76 | 2350 | 0.6729 | 0.8267 | |
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| 0.176 | 3.84 | 2400 | 0.6699 | 0.82 | |
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| 0.1815 | 3.92 | 2450 | 0.6819 | 0.8067 | |
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| 0.1987 | 4.0 | 2500 | 0.6543 | 0.8333 | |
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| 0.1236 | 4.08 | 2550 | 0.6686 | 0.8333 | |
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| 0.1599 | 4.16 | 2600 | 0.6583 | 0.8267 | |
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| 0.1256 | 4.24 | 2650 | 0.6871 | 0.8267 | |
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| 0.1291 | 4.32 | 2700 | 0.6855 | 0.82 | |
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| 0.1198 | 4.4 | 2750 | 0.6901 | 0.82 | |
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| 0.1245 | 4.48 | 2800 | 0.7152 | 0.8267 | |
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| 0.1784 | 4.56 | 2850 | 0.7053 | 0.82 | |
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| 0.1705 | 4.64 | 2900 | 0.7016 | 0.82 | |
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| 0.1265 | 4.72 | 2950 | 0.7013 | 0.82 | |
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| 0.1192 | 4.8 | 3000 | 0.7084 | 0.82 | |
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| 0.174 | 4.88 | 3050 | 0.7062 | 0.82 | |
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| 0.1328 | 4.96 | 3100 | 0.7061 | 0.82 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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