---
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: KUCI_albert_base_Finetuned
  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. -->

# KUCI_albert_base_Finetuned

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3234
- F1: 0.3702

## 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: 1e-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: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.3324        | 1.0   | 5196  | 1.3209          | 0.3606 |
| 1.3295        | 2.0   | 10392 | 1.3197          | 0.3729 |
| 1.324         | 3.0   | 15588 | 1.3194          | 0.3644 |
| 1.3244        | 4.0   | 20784 | 1.3218          | 0.3604 |
| 1.3201        | 5.0   | 25980 | 1.3195          | 0.3647 |
| 1.3135        | 6.0   | 31176 | 1.3210          | 0.3646 |
| 1.3124        | 7.0   | 36372 | 1.3234          | 0.3702 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1