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: 0.0015
- 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