---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google-bert/bert-large-uncased
metrics:
- accuracy
model-index:
- name: emotion-bert-large-uncased-balanced-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. -->

# emotion-bert-large-uncased-balanced-lora

This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1915
- Accuracy: 0.939

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 250  | 0.5079          | 0.833    |
| 0.7741        | 2.0   | 500  | 0.2768          | 0.913    |
| 0.7741        | 3.0   | 750  | 0.2100          | 0.929    |
| 0.2069        | 4.0   | 1000 | 0.1915          | 0.939    |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1