metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
base_model: roberta-large
model-index:
- name: roberta-large-lora-token-classification
results: []
roberta-large-lora-token-classification
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4772
- Precision: 0.7667
- Recall: 0.7573
- F1-score: 0.7620
- Accuracy: 0.7978
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6534 | 1.0 | 762 | 0.5813 | 0.5741 | 0.8633 | 0.6896 | 0.6678 |
| 0.5574 | 2.0 | 1524 | 0.6461 | 0.5373 | 0.8848 | 0.6686 | 0.6251 |
| 0.5534 | 3.0 | 2286 | 0.5031 | 0.6658 | 0.8264 | 0.7375 | 0.7485 |
| 0.5434 | 4.0 | 3048 | 0.4725 | 0.7818 | 0.7373 | 0.7589 | 0.7997 |
| 0.5531 | 5.0 | 3810 | 0.4772 | 0.7667 | 0.7573 | 0.7620 | 0.7978 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2