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

# COPA_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: 0.7959
- F1: 0.72

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 63   | 0.5853          | 0.728  |
| No log        | 2.0   | 126  | 0.5540          | 0.708  |
| No log        | 3.0   | 189  | 0.5356          | 0.74   |
| No log        | 4.0   | 252  | 0.5380          | 0.766  |
| No log        | 5.0   | 315  | 0.5841          | 0.7580 |
| No log        | 6.0   | 378  | 0.6396          | 0.738  |
| No log        | 7.0   | 441  | 0.6778          | 0.7420 |
| 0.2823        | 8.0   | 504  | 0.7111          | 0.728  |
| 0.2823        | 9.0   | 567  | 0.7695          | 0.712  |
| 0.2823        | 10.0  | 630  | 0.7959          | 0.72   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1