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---
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: 0.0416
- Precision: 0.9291
- Recall: 0.9704
- F1: 0.9493
- Accuracy: 0.9910
## 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: 4
- eval_batch_size: 4
- 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 | 184 | 0.0454 | 0.9154 | 0.8815 | 0.8981 | 0.9843 |
| No log | 2.0 | 368 | 0.0444 | 0.9220 | 0.9630 | 0.9420 | 0.9903 |
| 0.0654 | 3.0 | 552 | 0.0416 | 0.9291 | 0.9704 | 0.9493 | 0.9910 |
| 0.0654 | 4.0 | 736 | 0.0422 | 0.9489 | 0.9630 | 0.9559 | 0.9918 |
| 0.0654 | 5.0 | 920 | 0.0451 | 0.9416 | 0.9556 | 0.9485 | 0.9910 |
| 0.0064 | 6.0 | 1104 | 0.0461 | 0.9416 | 0.9556 | 0.9485 | 0.9910 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
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