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---
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