---
base_model: docketanalyzer/docket-lm-xs
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: label-complaint
  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. -->

# label-complaint

This model is a fine-tuned version of [docketanalyzer/docket-lm-xs](https://huggingface.co/docketanalyzer/docket-lm-xs) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0363
- F1: 0.9892

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0334        | 0.61  | 60   | 0.0383          | 0.9928 |
| 0.0077        | 1.22  | 120  | 0.0542          | 0.9786 |
| 0.004         | 1.84  | 180  | 0.0340          | 0.9892 |
| 0.0031        | 2.45  | 240  | 0.1027          | 0.9716 |
| 0.0019        | 3.06  | 300  | 0.0067          | 0.9964 |
| 0.0036        | 3.67  | 360  | 0.0076          | 0.9964 |
| 0.0019        | 4.29  | 420  | 0.0472          | 0.9856 |
| 0.1193        | 4.9   | 480  | 0.0503          | 0.9856 |
| 0.0014        | 5.51  | 540  | 0.0350          | 0.9892 |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.15.1