---
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: []
---

<!-- 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-token-classification

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