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--- |
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base_model: cardiffnlp/twitter-roberta-base-sentiment-latest |
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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: twitter-roberta-base-sentiment-latest |
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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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# twitter-roberta-base-sentiment-latest |
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3202 |
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- Accuracy: 0.7915 |
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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: 32 |
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- eval_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 600 |
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- num_epochs: 6 |
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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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| 0.8113 | 0.12 | 30 | 0.7971 | 0.418 | |
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| 0.6733 | 0.24 | 60 | 0.6551 | 0.469 | |
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| 0.5712 | 0.36 | 90 | 0.5713 | 0.522 | |
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| 0.5234 | 0.48 | 120 | 0.5311 | 0.565 | |
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| 0.5406 | 0.6 | 150 | 0.4938 | 0.6595 | |
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| 0.4856 | 0.72 | 180 | 0.4482 | 0.692 | |
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| 0.4732 | 0.84 | 210 | 0.4147 | 0.7185 | |
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| 0.4217 | 0.96 | 240 | 0.4038 | 0.726 | |
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| 0.4097 | 1.08 | 270 | 0.3828 | 0.7375 | |
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| 0.3911 | 1.2 | 300 | 0.3928 | 0.735 | |
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| 0.3779 | 1.32 | 330 | 0.3767 | 0.7555 | |
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| 0.3829 | 1.44 | 360 | 0.3705 | 0.74 | |
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| 0.3596 | 1.56 | 390 | 0.3905 | 0.744 | |
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| 0.3626 | 1.68 | 420 | 0.3712 | 0.7425 | |
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| 0.3763 | 1.8 | 450 | 0.3679 | 0.752 | |
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| 0.3722 | 1.92 | 480 | 0.3353 | 0.7805 | |
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| 0.3387 | 2.04 | 510 | 0.3504 | 0.768 | |
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| 0.3247 | 2.16 | 540 | 0.3573 | 0.766 | |
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| 0.3242 | 2.28 | 570 | 0.3526 | 0.7775 | |
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| 0.4003 | 2.4 | 600 | 0.3413 | 0.7785 | |
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| 0.353 | 2.52 | 630 | 0.3519 | 0.765 | |
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| 0.3557 | 2.64 | 660 | 0.3421 | 0.7845 | |
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| 0.3013 | 2.76 | 690 | 0.3291 | 0.7855 | |
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| 0.3034 | 2.88 | 720 | 0.3306 | 0.779 | |
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| 0.3146 | 3.0 | 750 | 0.3554 | 0.767 | |
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| 0.2856 | 3.12 | 780 | 0.3333 | 0.7825 | |
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| 0.2764 | 3.24 | 810 | 0.3353 | 0.7795 | |
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| 0.2844 | 3.36 | 840 | 0.3202 | 0.7915 | |
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| 0.2531 | 3.48 | 870 | 0.3388 | 0.7815 | |
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| 0.3134 | 3.6 | 900 | 0.3497 | 0.7775 | |
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| 0.2874 | 3.72 | 930 | 0.3427 | 0.787 | |
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| 0.2822 | 3.84 | 960 | 0.3328 | 0.7805 | |
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| 0.2963 | 3.96 | 990 | 0.3375 | 0.7885 | |
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| 0.2014 | 4.08 | 1020 | 0.3579 | 0.787 | |
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| 0.2275 | 4.2 | 1050 | 0.3472 | 0.7905 | |
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| 0.2758 | 4.32 | 1080 | 0.3497 | 0.7915 | |
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| 0.2552 | 4.44 | 1110 | 0.3555 | 0.775 | |
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| 0.228 | 4.56 | 1140 | 0.3494 | 0.784 | |
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| 0.2471 | 4.68 | 1170 | 0.3451 | 0.787 | |
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| 0.2505 | 4.8 | 1200 | 0.3508 | 0.7825 | |
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| 0.2453 | 4.92 | 1230 | 0.3539 | 0.785 | |
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| 0.2296 | 5.04 | 1260 | 0.3505 | 0.791 | |
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| 0.2449 | 5.16 | 1290 | 0.3602 | 0.7835 | |
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| 0.2171 | 5.28 | 1320 | 0.3630 | 0.782 | |
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| 0.237 | 5.4 | 1350 | 0.3552 | 0.789 | |
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| 0.1885 | 5.52 | 1380 | 0.3730 | 0.7795 | |
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| 0.2428 | 5.64 | 1410 | 0.3547 | 0.7925 | |
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| 0.225 | 5.76 | 1440 | 0.3586 | 0.7835 | |
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| 0.2513 | 5.88 | 1470 | 0.3586 | 0.786 | |
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| 0.2241 | 6.0 | 1500 | 0.3580 | 0.787 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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