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distilbert-base-uncased-sentiment-finetuned-memes-20epoch
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2252
- Accuracy: 0.8160
- Precision: 0.8165
- Recall: 0.8160
- F1: 0.8162
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5319 | 1.0 | 4293 | 0.5560 | 0.7699 | 0.7777 | 0.7699 | 0.7704 |
| 0.4627 | 2.0 | 8586 | 0.6588 | 0.7856 | 0.7868 | 0.7856 | 0.7860 |
| 0.3735 | 3.0 | 12879 | 0.8583 | 0.7835 | 0.7854 | 0.7835 | 0.7813 |
| 0.3549 | 4.0 | 17172 | 1.0078 | 0.7872 | 0.7869 | 0.7872 | 0.7866 |
| 0.2995 | 5.0 | 21465 | 1.0007 | 0.8024 | 0.8030 | 0.8024 | 0.8012 |
| 0.2579 | 6.0 | 25758 | 1.1501 | 0.8150 | 0.8152 | 0.8150 | 0.8151 |
| 0.2078 | 7.0 | 30051 | 1.2604 | 0.8097 | 0.8137 | 0.8097 | 0.8102 |
| 0.1635 | 8.0 | 34344 | 1.3755 | 0.8092 | 0.8092 | 0.8092 | 0.8085 |
| 0.1453 | 9.0 | 38637 | 1.4639 | 0.8097 | 0.8137 | 0.8097 | 0.8102 |
| 0.1431 | 10.0 | 42930 | 1.5612 | 0.8050 | 0.8048 | 0.8050 | 0.8044 |
| 0.085 | 11.0 | 47223 | 1.8216 | 0.8097 | 0.8121 | 0.8097 | 0.8101 |
| 0.0693 | 12.0 | 51516 | 1.7761 | 0.8087 | 0.8100 | 0.8087 | 0.8090 |
| 0.041 | 13.0 | 55809 | 1.8538 | 0.8082 | 0.8083 | 0.8082 | 0.8082 |
| 0.0391 | 14.0 | 60102 | 2.0022 | 0.8160 | 0.8158 | 0.8160 | 0.8158 |
| 0.0299 | 15.0 | 64395 | 2.0101 | 0.8124 | 0.8121 | 0.8124 | 0.8121 |
| 0.0226 | 16.0 | 68688 | 2.0396 | 0.8150 | 0.8152 | 0.8150 | 0.8151 |
| 0.0229 | 17.0 | 72981 | 2.1071 | 0.8171 | 0.8170 | 0.8171 | 0.8171 |
| 0.0133 | 18.0 | 77274 | 2.1047 | 0.8181 | 0.8182 | 0.8181 | 0.8182 |
| 0.0268 | 19.0 | 81567 | 2.2037 | 0.8208 | 0.8208 | 0.8208 | 0.8208 |
| 0.0068 | 20.0 | 85860 | 2.2252 | 0.8160 | 0.8165 | 0.8160 | 0.8162 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
