---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
- accuracy
- f1
model-index:
- name: lora_fine_tuned_cb
  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. -->

# lora_fine_tuned_cb

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4310
- Accuracy: 0.3182
- F1: 0.1536

## 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: 0.003
- 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: linear
- training_steps: 400

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.8568        | 3.5714  | 50   | 2.3106          | 0.3182   | 0.1536 |
| 0.8465        | 7.1429  | 100  | 1.3703          | 0.3182   | 0.1536 |
| 0.7884        | 10.7143 | 150  | 1.3701          | 0.3182   | 0.1536 |
| 0.7275        | 14.2857 | 200  | 1.5024          | 0.3182   | 0.1536 |
| 0.7691        | 17.8571 | 250  | 1.3990          | 0.3182   | 0.1536 |
| 0.742         | 21.4286 | 300  | 1.3898          | 0.3182   | 0.1536 |
| 0.7094        | 25.0    | 350  | 1.4059          | 0.3182   | 0.1536 |
| 0.7238        | 28.5714 | 400  | 1.4310          | 0.3182   | 0.1536 |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1