---
base_model: scales-okn/docket-language-model
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ontology-answer-test
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ontology-answer-test

This model is a fine-tuned version of [scales-okn/docket-language-model](https://huggingface.co./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