---
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: 0.0121
- F1: 0.9981

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0312        | 0.08  | 95   | 0.0374          | 0.9923 |
| 0.0035        | 0.16  | 190  | 0.0096          | 0.9981 |
| 0.0022        | 0.24  | 285  | 0.0068          | 0.9990 |
| 0.0016        | 0.32  | 380  | 0.0143          | 0.9971 |
| 0.0012        | 0.4   | 475  | 0.0124          | 0.9981 |
| 0.0013        | 0.48  | 570  | 0.0127          | 0.9981 |
| 0.0012        | 0.56  | 665  | 0.0114          | 0.9981 |
| 0.0011        | 0.64  | 760  | 0.0130          | 0.9981 |
| 0.001         | 0.72  | 855  | 0.0117          | 0.9981 |
| 0.0005        | 0.8   | 950  | 0.0130          | 0.9981 |
| 0.0005        | 0.88  | 1045 | 0.0118          | 0.9981 |
| 0.0005        | 0.96  | 1140 | 0.0126          | 0.9981 |


### Framework versions

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