metadata
base_model: scales-okn/docket-language-model
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ontology-answer-test
results: []
ontology-answer-test
This model is a fine-tuned version of scales-okn/docket-language-model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0009
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
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: 3e-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: 0.06
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0233 | 1.2903 | 100 | 0.0434 | 0.9862 | 0.9720 | 0.9630 | 0.9811 |
| 0.0007 | 2.5806 | 200 | 0.0072 | 0.9954 | 0.9905 | 1.0 | 0.9811 |
| 0.0003 | 3.8710 | 300 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1