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---
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
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