---
library_name: transformers
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: custom_model
  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. -->

# custom_model

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6805        | 0.5556 | 20   | 0.5965          | 0.7606   | 0         | 0.0    | 0      |
| 0.5306        | 1.1111 | 40   | 0.4812          | 0.7606   | 0         | 0.0    | 0      |
| 0.3863        | 1.6667 | 60   | 0.2857          | 0.7606   | 0         | 0.0    | 0      |
| 0.234         | 2.2222 | 80   | 0.1738          | 0.9437   | 1.0       | 0.7647 | 0.8667 |
| 0.0583        | 2.7778 | 100  | 0.0827          | 0.9859   | 1.0       | 0.9412 | 0.9697 |
| 0.0314        | 3.3333 | 120  | 0.0036          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0926        | 3.8889 | 140  | 0.0873          | 0.9718   | 1.0       | 0.8824 | 0.9375 |
| 0.0019        | 4.4444 | 160  | 0.0007          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0556        | 5.0    | 180  | 0.0009          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0018        | 5.5556 | 200  | 0.0467          | 0.9859   | 1.0       | 0.9412 | 0.9697 |
| 0.0011        | 6.1111 | 220  | 0.0005          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0012        | 6.6667 | 240  | 0.0004          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0011        | 7.2222 | 260  | 0.0004          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0012        | 7.7778 | 280  | 0.0004          | 1.0      | 1.0       | 1.0    | 1.0    |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1