File size: 2,097 Bytes
b235196
73de8fd
b235196
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
73bd912
 
b235196
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
73bd912
b235196
 
 
 
51a2059
73de8fd
73bd912
b235196
 
 
51a2059
 
73bd912
 
 
 
 
 
 
 
 
 
 
 
b235196
 
 
 
51a2059
 
b235196
73de8fd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
---
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: 0.0015
- F1: 0.9995

## 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0013        | 0.08  | 380  | 0.0054          | 0.9983 |
| 0.0007        | 0.16  | 760  | 0.0139          | 0.9976 |
| 0.0003        | 0.24  | 1140 | 0.0061          | 0.9985 |
| 0.0002        | 0.32  | 1520 | 0.0109          | 0.9981 |
| 0.0005        | 0.4   | 1900 | 0.0093          | 0.9985 |
| 0.0002        | 0.48  | 2280 | 0.0080          | 0.9988 |
| 0.0004        | 0.56  | 2660 | 0.0099          | 0.9978 |
| 0.0004        | 0.64  | 3040 | 0.0024          | 0.9990 |
| 0.0002        | 0.72  | 3420 | 0.0037          | 0.9988 |
| 0.0003        | 0.8   | 3800 | 0.0013          | 0.9998 |
| 0.0003        | 0.88  | 4180 | 0.0034          | 0.9993 |
| 0.0002        | 0.96  | 4560 | 0.0017          | 0.9993 |


### Framework versions

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