<!-- 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. -->
correct_twitter_RoBERTa_token_itr0_1e-05_essays_01_03_2022-15_32_16
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2663
- Precision: 0.3644
- Recall: 0.4985
- F1: 0.4210
- Accuracy: 0.8997
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 11 | 0.5174 | 0.0120 | 0.0061 | 0.0081 | 0.6997 |
No log | 2.0 | 22 | 0.4029 | 0.1145 | 0.3098 | 0.1672 | 0.8265 |
No log | 3.0 | 33 | 0.3604 | 0.2539 | 0.4448 | 0.3233 | 0.8632 |
No log | 4.0 | 44 | 0.3449 | 0.2992 | 0.4755 | 0.3673 | 0.8704 |
No log | 5.0 | 55 | 0.3403 | 0.3340 | 0.4816 | 0.3945 | 0.8760 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3