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

# e_care_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: 1.4498
- F1: 0.7290

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.552         | 1.0   | 933  | 0.5073          | 0.7380 |
| 0.392         | 2.0   | 1866 | 0.5267          | 0.7455 |
| 0.2009        | 3.0   | 2799 | 0.7612          | 0.7446 |
| 0.0715        | 4.0   | 3732 | 1.0338          | 0.7479 |
| 0.0243        | 5.0   | 4665 | 1.2592          | 0.7328 |
| 0.0079        | 6.0   | 5598 | 1.4134          | 0.7347 |
| 0.0035        | 7.0   | 6531 | 1.4498          | 0.7290 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1