---
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: 0.0635
- F1: 0.9828

## 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: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0787        | 1.42  | 60   | 0.0636          | 0.9739 |
| 0.0053        | 2.84  | 120  | 0.0489          | 0.9828 |
| 0.0029        | 4.26  | 180  | 0.0556          | 0.9828 |
| 0.0019        | 5.68  | 240  | 0.0636          | 0.9828 |
| 0.0014        | 7.1   | 300  | 0.0638          | 0.9828 |
| 0.0012        | 8.52  | 360  | 0.0635          | 0.9828 |
| 0.0012        | 9.94  | 420  | 0.0635          | 0.9828 |


### Framework versions

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