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

# multilabel_classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3550
- F1 Micro: 0.3846
- F1 Macro: 0.3832
- F1 Weighted: 0.3836
- Accuracy: 0.3008

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|
| No log        | 1.0   | 288  | 0.4072          | 0.0078   | 0.0074   | 0.0077      | 0.0859   |
| 0.4124        | 2.0   | 576  | 0.3695          | 0.2230   | 0.2164   | 0.2160      | 0.1914   |
| 0.4124        | 3.0   | 864  | 0.3614          | 0.3195   | 0.3123   | 0.3118      | 0.2578   |
| 0.3467        | 4.0   | 1152 | 0.3584          | 0.3580   | 0.3547   | 0.3539      | 0.2695   |
| 0.3467        | 5.0   | 1440 | 0.3550          | 0.3846   | 0.3832   | 0.3836      | 0.3008   |
| 0.3168        | 6.0   | 1728 | 0.3578          | 0.4127   | 0.4089   | 0.4091      | 0.3164   |
| 0.291         | 7.0   | 2016 | 0.3618          | 0.4136   | 0.4096   | 0.4099      | 0.3164   |
| 0.291         | 8.0   | 2304 | 0.3636          | 0.4175   | 0.4134   | 0.4137      | 0.3242   |
| 0.281         | 9.0   | 2592 | 0.3640          | 0.4235   | 0.4197   | 0.4201      | 0.3320   |
| 0.281         | 10.0  | 2880 | 0.3647          | 0.4125   | 0.4094   | 0.4096      | 0.3203   |


### Framework versions

- PEFT 0.11.1
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.15.1