---
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: 0.4877
- Precision: 0.8557
- Recall: 0.6375
- F1-score: 0.7306
- Accuracy: 0.7991

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.656         | 1.0   | 762  | 0.6091          | 0.5121    | 0.9432 | 0.6638   | 0.5916   |
| 0.5514        | 2.0   | 1524 | 0.6414          | 0.5205    | 0.9370 | 0.6692   | 0.6041   |
| 0.5584        | 3.0   | 2286 | 0.4862          | 0.7271    | 0.7696 | 0.7478   | 0.7781   |
| 0.5467        | 4.0   | 3048 | 0.4781          | 0.8197    | 0.6912 | 0.7500   | 0.8030   |
| 0.5519        | 5.0   | 3810 | 0.4877          | 0.8557    | 0.6375 | 0.7306   | 0.7991   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2