---
library_name: peft
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-banking77-classifier-lora
  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. -->

# bert-banking77-classifier-lora

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: 0.6999
- F1: 0.8264

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 16
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.3431        | 1.0   | 313  | 2.1174          | 0.3925 |
| 1.3737        | 2.0   | 626  | 1.2632          | 0.6508 |
| 0.9534        | 3.0   | 939  | 0.9034          | 0.7581 |
| 0.7365        | 4.0   | 1252 | 0.7530          | 0.8130 |
| 0.6526        | 5.0   | 1565 | 0.6999          | 0.8264 |


### Framework versions

- PEFT 0.10.0
- Transformers 4.49.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0