<!-- 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. -->
bert-nlp-project-imdb
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7986
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: 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: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.1745 | 0.37 | 453 | 2.9488 |
3.0364 | 0.75 | 906 | 2.9024 |
2.9915 | 1.12 | 1359 | 2.8552 |
2.9427 | 1.5 | 1812 | 2.8371 |
2.9247 | 1.87 | 2265 | 2.8125 |
2.902 | 2.25 | 2718 | 2.7948 |
2.8997 | 2.62 | 3171 | 2.8013 |
2.8914 | 3.0 | 3624 | 2.8113 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2