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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: []
---
<!-- 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: 1.7588
- Precision: 0.4745
- Recall: 0.1738
- F1: 0.2544
- Accuracy: 0.6770
## 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: 1
- eval_batch_size: 1
- 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 | 19 | 2.2673 | 0.3636 | 0.0214 | 0.0404 | 0.6355 |
| No log | 2.0 | 38 | 1.9224 | 0.3710 | 0.0615 | 0.1055 | 0.6459 |
| No log | 3.0 | 57 | 1.7588 | 0.4745 | 0.1738 | 0.2544 | 0.6770 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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