---
library_name: peft
license: apache-2.0
base_model: bert-base-uncased
tags:
- base_model:adapter:bert-base-uncased
- lora
- transformers
metrics:
- accuracy
- f1
model-index:
- name: imdb-lora-0.1
  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. -->

# imdb-lora-0.1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6777
- Accuracy: 0.6072
- F1: 0.6071

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 40   | 0.6947          | 0.5022   | 0.5014 |
| 0.7014        | 2.0   | 80   | 0.6892          | 0.5315   | 0.5190 |
| 0.6915        | 3.0   | 120  | 0.6838          | 0.5758   | 0.5744 |
| 0.6886        | 4.0   | 160  | 0.6795          | 0.5976   | 0.5971 |
| 0.6839        | 5.0   | 200  | 0.6777          | 0.6072   | 0.6071 |


### Framework versions

- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1