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---
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
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