Randomized_Bert_Stacked_model_20
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2269
- F1: 0.4960
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: 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 316 | 1.2874 | 0.4517 |
| 1.3332 | 2.0 | 632 | 1.2514 | 0.4728 |
| 1.3332 | 3.0 | 948 | 1.2356 | 0.4887 |
| 1.2664 | 4.0 | 1264 | 1.2268 | 0.4930 |
| 1.2288 | 5.0 | 1580 | 1.2269 | 0.4960 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1