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---
license: apache-2.0
base_model: PartAI/TookaBERT-Base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_model
results: []
language:
- fa
pipeline_tag: token-classification
---
<!-- 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. -->
# my_model
This model is a fine-tuned version of [PartAI/TookaBERT-Base](https://huggingface.co/PartAI/TookaBERT-Base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3774
- Precision: 0.2
- Recall: 0.0909
- F1: 0.1250
- Accuracy: 0.5319
## 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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 2 | 2.8942 | 0.0 | 0.0 | 0.0 | 0.3830 |
| No log | 2.0 | 4 | 2.5283 | 0.0 | 0.0 | 0.0 | 0.4894 |
| No log | 3.0 | 6 | 2.3774 | 0.2 | 0.0909 | 0.1250 | 0.5319 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1