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---
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 |