metadata
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: 0.0635
- F1: 0.9828
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: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0787 | 1.42 | 60 | 0.0636 | 0.9739 |
| 0.0053 | 2.84 | 120 | 0.0489 | 0.9828 |
| 0.0029 | 4.26 | 180 | 0.0556 | 0.9828 |
| 0.0019 | 5.68 | 240 | 0.0636 | 0.9828 |
| 0.0014 | 7.1 | 300 | 0.0638 | 0.9828 |
| 0.0012 | 8.52 | 360 | 0.0635 | 0.9828 |
| 0.0012 | 9.94 | 420 | 0.0635 | 0.9828 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.15.1