Alesteba's picture
update model card README.md
9066478
---
license: apache-2.0
tags:
- classifier
- generated_from_trainer
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: deep_model_09_clasificador-news-2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ag_news
type: ag_news
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9033149171270718
---
<!-- 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. -->
# deep_model_09_clasificador-news-2
This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4530
- Accuracy: 0.9033
## 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: 5e-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: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6332 | 1.0 | 715 | 0.4676 | 0.8812 |
| 0.5148 | 2.0 | 1430 | 0.4496 | 0.9006 |
| 0.3638 | 3.0 | 2145 | 0.4530 | 0.9033 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3