---
license: mit
tags:
- generated_from_trainer
model-index:
- name: contract-ner-model-da
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# contract-ner-model-da

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0026
- Micro F1: 0.9297

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 919
- num_epochs: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Micro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8971        | 0.24  | 200  | 0.0205          | 0.0      |
| 0.0173        | 0.48  | 400  | 0.0100          | 0.2921   |
| 0.0092        | 0.73  | 600  | 0.0065          | 0.7147   |
| 0.0063        | 0.97  | 800  | 0.0046          | 0.8332   |
| 0.0047        | 1.21  | 1000 | 0.0047          | 0.8459   |
| 0.0042        | 1.45  | 1200 | 0.0039          | 0.8694   |
| 0.0037        | 1.69  | 1400 | 0.0035          | 0.8888   |
| 0.0032        | 1.93  | 1600 | 0.0035          | 0.8840   |
| 0.0025        | 2.18  | 1800 | 0.0029          | 0.8943   |
| 0.0023        | 2.42  | 2000 | 0.0024          | 0.9104   |
| 0.0023        | 2.66  | 2200 | 0.0032          | 0.8808   |
| 0.0021        | 2.9   | 2400 | 0.0022          | 0.9338   |
| 0.0018        | 3.14  | 2600 | 0.0020          | 0.9315   |
| 0.0015        | 3.39  | 2800 | 0.0026          | 0.9297   |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.8.1+cu101
- Datasets 1.12.1
- Tokenizers 0.10.3