---
library_name: peft
license: apache-2.0
base_model:
- ykacer/bert-base-cased-imdb-sequence-classification
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lora_training
  results: []
language:
- en
pipeline_tag: token-classification
---

<!-- 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. -->

# lora_training

This model is a fine-tuned version of [ykacer/bert-base-cased-imdb-sequence-classification](https://huggingface.co/ykacer/bert-base-cased-imdb-sequence-classification) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0969
- Accuracy: 0.5975

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6038        | 1.0   | 800  | 1.5082          | 0.4547   |
| 1.305         | 2.0   | 1600 | 1.2096          | 0.5466   |
| 1.1727        | 3.0   | 2400 | 1.1352          | 0.5775   |
| 1.1199        | 4.0   | 3200 | 1.1062          | 0.5947   |
| 1.0959        | 5.0   | 4000 | 1.0969          | 0.5975   |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3