---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: murat_nerscratch1903model_son
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# murat_nerscratch1903model_son

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1105
- Precision: 0.9301
- Recall: 0.9457
- F1: 0.9377

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
| 1.1229        | 1.0   | 9906  | 0.1297          | 0.9198    | 0.9340 | 0.9268 |
| 0.3449        | 2.0   | 19812 | 0.1105          | 0.9301    | 0.9457 | 0.9377 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1