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raw_disaster_tweets
aellxx/raw_disaster_tweets
raw_disaster_tweets is a text classification model from aellxx. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Apr 18, 2023
- Updated
- Apr 26, 2023
- SHA
- b93fe692
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
raw_disaster_tweets
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4184
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7201 | 0.12 | 12 | 0.7164 |
| 0.7234 | 0.25 | 24 | 0.7148 |
| 0.7128 | 0.38 | 36 | 0.7121 |
| 0.7122 | 0.5 | 48 | 0.7086 |
| 0.7074 | 0.62 | 60 | 0.7042 |
| 0.699 | 0.75 | 72 | 0.6990 |
| 0.6989 | 0.88 | 84 | 0.6934 |
| 0.6904 | 1.0 | 96 | 0.6871 |
| 0.6884 | 1.12 | 108 | 0.6801 |
| 0.6793 | 1.25 | 120 | 0.6723 |
| 0.6746 | 1.38 | 132 | 0.6638 |
| 0.6635 | 1.5 | 144 | 0.6539 |
| 0.647 | 1.62 | 156 | 0.6426 |
| 0.6418 | 1.75 | 168 | 0.6293 |
| 0.6287 | 1.88 | 180 | 0.6140 |
| 0.5938 | 2.0 | 192 | 0.5959 |
| 0.5869 | 2.12 | 204 | 0.5768 |
| 0.5718 | 2.25 | 216 | 0.5586 |
| 0.5638 | 2.38 | 228 | 0.5413 |
| 0.5265 | 2.5 | 240 | 0.5259 |
| 0.5165 | 2.62 | 252 | 0.5111 |
| 0.4966 | 2.75 | 264 | 0.4987 |
| 0.5072 | 2.88 | 276 | 0.4886 |
| 0.456 | 3.0 | 288 | 0.4827 |
| 0.458 | 3.12 | 300 | 0.4704 |
| 0.434 | 3.25 | 312 | 0.4647 |
| 0.421 | 3.38 | 324 | 0.4604 |
| 0.4679 | 3.5 | 336 | 0.4546 |
| 0.4463 | 3.62 | 348 | 0.4498 |
| 0.4288 | 3.75 | 360 | 0.4500 |
| 0.4261 | 3.88 | 372 | 0.4406 |
| 0.4314 | 4.0 | 384 | 0.4420 |
| 0.3848 | 4.12 | 396 | 0.4349 |
| 0.4145 | 4.25 | 408 | 0.4354 |
| 0.4151 | 4.38 | 420 | 0.4277 |
| 0.4034 | 4.5 | 432 | 0.4273 |
| 0.3933 | 4.62 | 444 | 0.4295 |
| 0.4171 | 4.75 | 456 | 0.4216 |
| 0.3926 | 4.88 | 468 | 0.4179 |
| 0.3739 | 5.0 | 480 | 0.4184 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Apr 18, 2023
- Updated
- Apr 26, 2023