imdb-lora-0.1
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6777
- Accuracy: 0.6072
- F1: 0.6071
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 40 | 0.6947 | 0.5022 | 0.5014 |
| 0.7014 | 2.0 | 80 | 0.6892 | 0.5315 | 0.5190 |
| 0.6915 | 3.0 | 120 | 0.6838 | 0.5758 | 0.5744 |
| 0.6886 | 4.0 | 160 | 0.6795 | 0.5976 | 0.5971 |
| 0.6839 | 5.0 | 200 | 0.6777 | 0.6072 | 0.6071 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
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Base model
google-bert/bert-base-uncased