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preprocessed_disaster_tweets
aellxx/preprocessed_disaster_tweets
preprocessed_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
- 9f6ac141
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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. -->
preprocessed_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: 0.4125
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 |
|---|---|---|---|
| 0.6693 | 0.12 | 12 | 0.6626 |
| 0.6712 | 0.25 | 24 | 0.6614 |
| 0.6604 | 0.38 | 36 | 0.6595 |
| 0.6667 | 0.5 | 48 | 0.6571 |
| 0.6574 | 0.62 | 60 | 0.6540 |
| 0.6595 | 0.75 | 72 | 0.6500 |
| 0.6545 | 0.88 | 84 | 0.6456 |
| 0.6502 | 1.0 | 96 | 0.6405 |
| 0.6437 | 1.12 | 108 | 0.6347 |
| 0.6393 | 1.25 | 120 | 0.6280 |
| 0.6496 | 1.38 | 132 | 0.6218 |
| 0.6196 | 1.5 | 144 | 0.6146 |
| 0.6299 | 1.62 | 156 | 0.6068 |
| 0.6068 | 1.75 | 168 | 0.5976 |
| 0.6038 | 1.88 | 180 | 0.5878 |
| 0.5786 | 2.0 | 192 | 0.5770 |
| 0.5691 | 2.12 | 204 | 0.5663 |
| 0.5619 | 2.25 | 216 | 0.5552 |
| 0.5758 | 2.38 | 228 | 0.5442 |
| 0.5249 | 2.5 | 240 | 0.5326 |
| 0.5264 | 2.62 | 252 | 0.5207 |
| 0.5167 | 2.75 | 264 | 0.5090 |
| 0.5259 | 2.88 | 276 | 0.4991 |
| 0.4738 | 3.0 | 288 | 0.4917 |
| 0.4681 | 3.12 | 300 | 0.4795 |
| 0.4482 | 3.25 | 312 | 0.4698 |
| 0.4354 | 3.38 | 324 | 0.4616 |
| 0.465 | 3.5 | 336 | 0.4531 |
| 0.4593 | 3.62 | 348 | 0.4469 |
| 0.4294 | 3.75 | 360 | 0.4467 |
| 0.4284 | 3.88 | 372 | 0.4374 |
| 0.4337 | 4.0 | 384 | 0.4347 |
| 0.3805 | 4.12 | 396 | 0.4318 |
| 0.4113 | 4.25 | 408 | 0.4269 |
| 0.4155 | 4.38 | 420 | 0.4201 |
| 0.4112 | 4.5 | 432 | 0.4205 |
| 0.3921 | 4.62 | 444 | 0.4228 |
| 0.4018 | 4.75 | 456 | 0.4151 |
| 0.3995 | 4.88 | 468 | 0.4102 |
| 0.3891 | 5.0 | 480 | 0.4125 |
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