metadata

license: apache-2.0
base_model: docketanalyzer/docket-lm-xs
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: label-complaint
    results: []

label-complaint

This model is a fine-tuned version of docketanalyzer/docket-lm-xs on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0230
F1: 0.9915

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_steps: 100
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.0112	0.0418	300	0.0576	0.9771
0.0551	0.0836	600	0.0362	0.9857
0.2331	0.1254	900	0.0354	0.9839
0.0009	0.1672	1200	0.0396	0.9868
0.005	0.2090	1500	0.0526	0.9867
0.0948	0.2508	1800	0.0434	0.9865
0.016	0.2926	2100	0.0297	0.9876
0.0047	0.3344	2400	0.0394	0.9882
0.0007	0.3763	2700	0.0422	0.9864
0.0037	0.4181	3000	0.0248	0.9910
0.002	0.4599	3300	0.0271	0.9909
0.0005	0.5017	3600	0.0283	0.9902
0.0155	0.5435	3900	0.0227	0.9910
0.0017	0.5853	4200	0.0290	0.9907
0.0002	0.6271	4500	0.0264	0.9899
0.0051	0.6689	4800	0.0294	0.9907
0.0152	0.7107	5100	0.0253	0.9903
0.0096	0.7525	5400	0.0232	0.9909
0.1812	0.7943	5700	0.0295	0.9915
0.0007	0.8361	6000	0.0235	0.9912
0.0081	0.8779	6300	0.0247	0.9910
0.0684	0.9197	6600	0.0236	0.9905
0.0003	0.9615	6900	0.0230	0.9914

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.14.4
Tokenizers 0.19.1