---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-v3-base-financial-inc-dec-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. -->

# deberta-v3-base-financial-inc-dec-ner

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0351
- Precision: 0.9051
- Recall: 0.9185
- F1: 0.9118
- Accuracy: 0.9873

## 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: 1e-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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 92   | 0.0589          | 0.8370    | 0.8370 | 0.8370 | 0.9813   |
| No log        | 2.0   | 184  | 0.0351          | 0.9051    | 0.9185 | 0.9118 | 0.9873   |
| No log        | 3.0   | 276  | 0.0626          | 0.8849    | 0.9111 | 0.8978 | 0.9828   |
| No log        | 4.0   | 368  | 0.0379          | 0.9357    | 0.9704 | 0.9527 | 0.9910   |
| No log        | 5.0   | 460  | 0.0384          | 0.9353    | 0.9630 | 0.9489 | 0.9903   |
| 0.0721        | 6.0   | 552  | 0.0421          | 0.9353    | 0.9630 | 0.9489 | 0.9903   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1