---
license: apache-2.0
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: 0.0064
- F1: 0.9987

## 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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.016         | 0.08  | 380  | 0.0157          | 0.9965 |
| 0.0006        | 0.16  | 760  | 0.0150          | 0.9975 |
| 0.0007        | 0.24  | 1140 | 0.0136          | 0.9977 |
| 0.0003        | 0.32  | 1520 | 0.0128          | 0.9982 |
| 0.0005        | 0.4   | 1900 | 0.0110          | 0.9985 |
| 0.0004        | 0.48  | 2280 | 0.0053          | 0.9987 |
| 0.0004        | 0.56  | 2660 | 0.0035          | 0.9995 |
| 0.0003        | 0.64  | 3040 | 0.0049          | 0.9987 |
| 0.0004        | 0.72  | 3420 | 0.0080          | 0.9985 |
| 0.0577        | 0.8   | 3800 | 0.0081          | 0.9982 |
| 0.0002        | 0.88  | 4180 | 0.0077          | 0.9987 |
| 0.0002        | 0.96  | 4560 | 0.0063          | 0.9987 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.14.4
- Tokenizers 0.19.1