---
license: apache-2.0
base_model: sileod/mdeberta-v3-base-tasksource-nli
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-trainer-persian
  results: []
language:
- fa
- en
---

<!-- 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. -->

# test-trainer-persian

This model is a fine-tuned version of [sileod/mdeberta-v3-base-tasksource-nli](https://huggingface.co./sileod/mdeberta-v3-base-tasksource-nli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1753
- Accuracy: 0.9463

{'قانون': 3241,
 'ادبیات': 18297,
 'دارو': 708,
 'شعر': 256,
 'سیاست': 5720,
 'دین': 911,
 'علم': 4546,
 'گفتگو': 2882}
 
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.514         | 1.0   | 1708 | 0.3680          | 0.8829   |
| 0.3639        | 2.0   | 3416 | 0.2282          | 0.9263   |
| 0.2534        | 3.0   | 5124 | 0.1753          | 0.9463   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1