metadata
library_name: peft
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
model-index:
- name: roberta-large-lora-multi-class-classification
results: []
roberta-large-lora-multi-class-classification
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2042
- Micro f1: 0.7842
- Macro f1: 0.5733
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
|---|---|---|---|---|---|
| 0.4408 | 0.9995 | 1048 | 0.2138 | 0.7841 | 0.5624 |
| 0.448 | 2.0 | 2097 | 0.2127 | 0.7943 | 0.5788 |
| 0.446 | 2.9986 | 3144 | 0.2042 | 0.7842 | 0.5733 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1