Alec Sánchez Montero
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---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
- pop science
model-index:
- name: results
results: []
language:
- es
metrics:
- f1
- roc_auc
pipeline_tag: text-classification
datasets:
- teoremaclon/popscitweetsbyarea
library_name: transformers
---
<!-- 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. -->
# results
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1582
- Roc Auc: 0.7868
- Hamming Loss: 0.0625
- F1 Score: 0.6231
## Model description
Label interpretation:
'astronomía y espacio' (astronomy and space): 0,
'matemáticas' (mathematics): 1,
'física' (physics): 2,
'biología' (biology): 3,
'medicina y salud' (health and medicine): 4,
'tecnología' (technology): 5,
'química' (chemistry): 6,
'historia de la ciencia' (history of science): 7,
'ingeniería' (engineering): 8,
'computación' (computation): 9,
'ciencias de la tierra' (earth science): 10,
'materia y energia' (matter and energy): 11,
'psicología' (psychology): 12,
'invitación a evento o a recursos' (invitation to event or resources): 13,
'efeméride' (anniversary/day of): 14,
'mujeres en la ciencia' (women in science): 15,
'cultura pop' (pop culture): 16,
'otro' (other): 17
## 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
### Training results
### Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Tokenizers 0.15.2