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

# emotions_bert_qlora

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5184
- F1 Micro: 0.6855
- F1 Macro: 0.6029
- Accuracy: 0.2129

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.8094        | 0.4082 | 20   | 0.7752          | 0.4570   | 0.1865   | 0.0990   |
| 0.7206        | 0.8163 | 40   | 0.6446          | 0.5938   | 0.3669   | 0.1230   |
| 0.6381        | 1.2245 | 60   | 0.6094          | 0.6163   | 0.4260   | 0.1159   |
| 0.5836        | 1.6327 | 80   | 0.5757          | 0.6345   | 0.4702   | 0.1553   |
| 0.5631        | 2.0408 | 100  | 0.5504          | 0.6674   | 0.5290   | 0.1922   |
| 0.5132        | 2.4490 | 120  | 0.5355          | 0.6686   | 0.5440   | 0.1922   |
| 0.504         | 2.8571 | 140  | 0.5260          | 0.6710   | 0.5843   | 0.1780   |
| 0.4853        | 3.2653 | 160  | 0.5209          | 0.6689   | 0.5854   | 0.1858   |
| 0.4494        | 3.6735 | 180  | 0.5165          | 0.6759   | 0.5942   | 0.1909   |
| 0.4663        | 4.0816 | 200  | 0.5146          | 0.6834   | 0.5900   | 0.2      |
| 0.4361        | 4.4898 | 220  | 0.5073          | 0.6876   | 0.6013   | 0.2214   |
| 0.4278        | 4.8980 | 240  | 0.5112          | 0.6830   | 0.6018   | 0.2045   |
| 0.4175        | 5.3061 | 260  | 0.5119          | 0.6775   | 0.5929   | 0.2013   |
| 0.4           | 5.7143 | 280  | 0.5118          | 0.6846   | 0.5961   | 0.2039   |
| 0.4088        | 6.1224 | 300  | 0.5100          | 0.6819   | 0.6015   | 0.2117   |
| 0.3811        | 6.5306 | 320  | 0.5211          | 0.6759   | 0.5952   | 0.1916   |
| 0.389         | 6.9388 | 340  | 0.5152          | 0.6770   | 0.6004   | 0.1974   |
| 0.3806        | 7.3469 | 360  | 0.5183          | 0.6853   | 0.6029   | 0.2123   |
| 0.3686        | 7.7551 | 380  | 0.5222          | 0.6739   | 0.5940   | 0.2019   |
| 0.3719        | 8.1633 | 400  | 0.5207          | 0.6777   | 0.5941   | 0.2091   |
| 0.3538        | 8.5714 | 420  | 0.5242          | 0.6765   | 0.5943   | 0.2006   |
| 0.3591        | 8.9796 | 440  | 0.5247          | 0.6784   | 0.5953   | 0.2091   |
| 0.3554        | 9.3878 | 460  | 0.5259          | 0.6815   | 0.5978   | 0.2142   |
| 0.346         | 9.7959 | 480  | 0.5256          | 0.6809   | 0.5976   | 0.2142   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1