metadata
library_name: peft
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: results_multilabel_lora
results: []
results_multilabel_lora
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: 0.3776
- Exact Match Accuracy: 0.76
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 50 | 0.4173 | 0.75 |
| No log | 2.0 | 100 | 0.3948 | 0.75 |
| No log | 3.0 | 150 | 0.3874 | 0.76 |
| No log | 4.0 | 200 | 0.3834 | 0.76 |
| No log | 5.0 | 250 | 0.3807 | 0.76 |
| No log | 6.0 | 300 | 0.3797 | 0.76 |
| No log | 7.0 | 350 | 0.3788 | 0.76 |
| No log | 8.0 | 400 | 0.3779 | 0.76 |
| No log | 9.0 | 450 | 0.3777 | 0.76 |
| 0.3811 | 10.0 | 500 | 0.3776 | 0.76 |
Framework versions
- PEFT 0.14.0
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1