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

This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1651
- Accuracy: 0.9315

## 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  | 0.4509          | 0.848    |
| 0.6387        | 2.0   | 500  | 0.2250          | 0.9225   |
| 0.6387        | 3.0   | 750  | 0.1771          | 0.9215   |
| 0.1705        | 4.0   | 1000 | 0.1651          | 0.9315   |


### Framework versions

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