---
library_name: peft
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
model-index:
- name: roberta-large-lora-multi-class-classification
  results: []
---

<!-- 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. -->

# roberta-large-lora-multi-class-classification

This model is a fine-tuned version of [roberta-large](https://huggingface.co/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