transformers tensorboard bart text2text-generation generated_from_trainer summarization es base_model:vgaraujov/bart-base-spanish base_model:finetune:vgaraujov/bart-base-spanish license:other autotrain_compatible endpoints_compatible region:us
---
base_model: vgaraujov/bart-base-spanish
language:
- es
library_name: transformers
license: other
metrics:
- rouge
pipeline_tag: summarization
tags:
- generated_from_trainer
widget:
- text: "summarize: Operador: 911, ¿cuál es su emergencia? \nPersona: ¡Ayuda! Mi casa\
    \ está en llamas.\nOperador: ¿Manténgase calmado. ¿Hay alguien atrapado dentro?\
    \ \nPersona: Sí, mi esposa y mis dos hijos están en el segundo piso. \nOperador:\
    \ ¿Puede salir de la casa? \nPersona: No, el fuego está bloqueando la salida.\
    \ \nOperador: No se preocupe, la ayuda está en camino. ¿En qué dirección se encuentra?\
    \ \nPersona: Estoy en la calle Mayor, número 123. \nOperador: ¿Es un edificio\
    \ de apartamentos o una casa unifamiliar? \nPersona: Es una casa unifamiliar.\
    \ \nOperador: ¿Hay algo más que deba saber? \nPersona: No, solo vengan rápido.\
    \ \nOperador: No se preocupe, ya están en camino. Mantenga la calma y siga las\
    \ instrucciones de los bomberos cuando lleguen. \nPersona: Gracias."
  example_title: Example 1
- text: 'summarize: Buenas noches, ayuda por favor a mi papá le están dando convulsiones
    y no puede respirar.'
  example_title: Example 2
model-index:
- name: bart_es_keys
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bart_es_keys

This model is a fine-tuned version of [vgaraujov/bart-base-spanish](https://huggingface.co/vgaraujov/bart-base-spanish).
It achieves the following results on the evaluation set:
- Loss: 1.3818
- Rouge1: 63.6736
- Rouge2: 37.301
- Rougel: 63.0481
- Rougelsum: 62.97
- Gen Len: 7.6

## Model description

This checkpoint extracts keywords or context from emergency transcribed calls.
Add the prefix "summarize: " before a test text to see the checkpoint's responses.

## Intended uses & limitations

Under privacy agreement.

## Training and evaluation data

Training data used has been provided by the ECU 911 service under a strict confidentiality agreement.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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 | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.4822        | 1.0   | 50   | 1.5713          | 51.0101 | 26.2004 | 50.4041 | 50.4791   | 7.33    |
| 1.5446        | 2.0   | 100  | 1.4584          | 57.2195 | 31.0281 | 56.4802 | 56.4801   | 7.75    |
| 1.2388        | 3.0   | 150  | 1.3971          | 61.0085 | 34.3564 | 60.1558 | 60.1153   | 7.84    |
| 1.0489        | 4.0   | 200  | 1.3611          | 62.0307 | 35.323  | 61.3034 | 61.1902   | 7.53    |
| 0.8992        | 5.0   | 250  | 1.3973          | 62.8046 | 37.3484 | 62.2618 | 62.2231   | 7.845   |
| 0.8357        | 6.0   | 300  | 1.3836          | 63.2165 | 36.9899 | 62.7019 | 62.5911   | 7.825   |
| 0.7731        | 7.0   | 350  | 1.3818          | 63.6736 | 37.301  | 63.0481 | 62.97     | 7.6     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0