---
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 [renjithks/distilbert-cord-ner](https://huggingface.co/renjithks/distilbert-cord-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2930
- Precision: 0.5096
- Recall: 0.4852
- F1: 0.4971
- Accuracy: 0.9275

## 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   | 22   | 0.3635          | 0.2888    | 0.0945 | 0.1424 | 0.8866   |
| No log        | 2.0   | 44   | 0.2795          | 0.3213    | 0.3018 | 0.3113 | 0.8982   |
| No log        | 3.0   | 66   | 0.2432          | 0.4243    | 0.4034 | 0.4136 | 0.9161   |
| No log        | 4.0   | 88   | 0.2446          | 0.4615    | 0.4654 | 0.4635 | 0.9193   |
| No log        | 5.0   | 110  | 0.2410          | 0.5143    | 0.4810 | 0.4971 | 0.9293   |
| No log        | 6.0   | 132  | 0.2598          | 0.5283    | 0.4612 | 0.4925 | 0.9305   |
| No log        | 7.0   | 154  | 0.2963          | 0.5230    | 0.4485 | 0.4829 | 0.9268   |
| No log        | 8.0   | 176  | 0.2753          | 0.4928    | 0.4838 | 0.4883 | 0.9283   |
| No log        | 9.0   | 198  | 0.2897          | 0.5194    | 0.4725 | 0.4948 | 0.9295   |
| No log        | 10.0  | 220  | 0.2930          | 0.5096    | 0.4852 | 0.4971 | 0.9275   |


### Framework versions

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