---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: fin_techgroup
  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. -->

# fin_techgroup

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0571
- Accuracy: 0.9765
- F1: 0.9765
- Precision: 0.9765
- Recall: 0.9765

## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 64   | 0.1279          | 0.9314   | 0.9345 | 0.9318    | 0.9373 |
| No log        | 2.0   | 128  | 0.0711          | 0.9667   | 0.9667 | 0.9667    | 0.9667 |
| No log        | 3.0   | 192  | 0.0786          | 0.9618   | 0.9628 | 0.9618    | 0.9637 |
| No log        | 4.0   | 256  | 0.0513          | 0.9775   | 0.9775 | 0.9775    | 0.9775 |
| No log        | 5.0   | 320  | 0.0616          | 0.9716   | 0.9721 | 0.9716    | 0.9725 |
| No log        | 6.0   | 384  | 0.0596          | 0.9765   | 0.9765 | 0.9765    | 0.9765 |
| No log        | 7.0   | 448  | 0.0612          | 0.9765   | 0.9765 | 0.9765    | 0.9765 |
| 0.0727        | 8.0   | 512  | 0.0571          | 0.9765   | 0.9765 | 0.9765    | 0.9765 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1