---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-expense-ner
  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. -->

# distilbert-expense-ner

This model is a fine-tuned version of [Geotrend/distilbert-base-en-fr-de-no-da-cased](https://huggingface.co/Geotrend/distilbert-base-en-fr-de-no-da-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1641
- Precision: 0.9489
- Recall: 0.9430
- F1: 0.9459
- Accuracy: 0.9721

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 112  | 0.1750          | 0.8720    | 0.8891 | 0.8805 | 0.9446   |
| No log        | 2.0   | 224  | 0.1339          | 0.8804    | 0.9078 | 0.8939 | 0.9515   |
| No log        | 3.0   | 336  | 0.1157          | 0.9315    | 0.9295 | 0.9305 | 0.9666   |
| No log        | 4.0   | 448  | 0.1291          | 0.9269    | 0.9326 | 0.9298 | 0.9666   |
| 0.2164        | 5.0   | 560  | 0.1400          | 0.9247    | 0.9285 | 0.9266 | 0.9666   |
| 0.2164        | 6.0   | 672  | 0.1463          | 0.9376    | 0.9347 | 0.9362 | 0.9689   |
| 0.2164        | 7.0   | 784  | 0.1463          | 0.9327    | 0.9337 | 0.9332 | 0.9694   |
| 0.2164        | 8.0   | 896  | 0.1711          | 0.9376    | 0.9337 | 0.9356 | 0.9661   |
| 0.0274        | 9.0   | 1008 | 0.1621          | 0.9421    | 0.9440 | 0.9431 | 0.9735   |
| 0.0274        | 10.0  | 1120 | 0.1641          | 0.9489    | 0.9430 | 0.9459 | 0.9721   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1