distilbert-base-uncased_3epoch
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6667
- Accuracy: 0.7233
- F1: 0.3642
- Precision: 0.5340
- Recall: 0.2764
- Precision Sarcastic: 0.5340
- Recall Sarcastic: 0.2764
- F1 Sarcastic: 0.3642
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
---|---|---|---|---|---|---|---|---|---|---|
No log | 1.0 | 174 | 0.5840 | 0.7133 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 2.0 | 348 | 0.6031 | 0.7161 | 0.1688 | 0.5263 | 0.1005 | 0.5263 | 0.1005 | 0.1688 |
0.4556 | 3.0 | 522 | 0.6667 | 0.7233 | 0.3642 | 0.5340 | 0.2764 | 0.5340 | 0.2764 | 0.3642 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.