---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-base-Label_B-768-epochs-5
  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-Label_B-768-epochs-5

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: 0.0609
- Accuracy: 0.9876
- F1: 0.9876
- Precision: 0.9877
- Recall: 0.9876

## 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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1209        | 0.9995 | 1066 | 0.3304          | 0.9204   | 0.9188 | 0.9333    | 0.9204 |
| 0.0639        | 2.0    | 2133 | 0.1217          | 0.9658   | 0.9658 | 0.9688    | 0.9658 |
| 0.0208        | 2.9995 | 3199 | 0.0540          | 0.9856   | 0.9856 | 0.9858    | 0.9856 |
| 0.002         | 4.0    | 4266 | 0.0609          | 0.9876   | 0.9876 | 0.9877    | 0.9876 |
| 0.0003        | 4.9977 | 5330 | 0.0786          | 0.9847   | 0.9847 | 0.9850    | 0.9847 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0