metadata

library_name: transformers
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: mi-super-modelo
    results: []

mi-super-modelo

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3257
Accuracy: 0.865

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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7019	0.04	5	0.6916	0.51
0.7006	0.08	10	0.6860	0.495
0.7015	0.12	15	0.6802	0.58
0.6842	0.16	20	0.6756	0.525
0.658	0.2	25	0.6492	0.595
0.6329	0.24	30	0.5335	0.855
0.4345	0.28	35	0.4493	0.825
0.3086	0.32	40	0.3973	0.84
0.4788	0.36	45	0.3747	0.855
0.6449	0.4	50	0.4614	0.8
0.2355	0.44	55	0.3603	0.855
0.4233	0.48	60	0.4841	0.8
0.5185	0.52	65	0.5940	0.755
0.3089	0.56	70	0.3760	0.87
0.3867	0.6	75	0.3636	0.86
0.3289	0.64	80	0.3339	0.885
0.5774	0.68	85	0.3070	0.875
0.3258	0.72	90	0.4532	0.8
0.5363	0.76	95	0.3687	0.86
0.4099	0.8	100	0.2847	0.88
0.2841	0.84	105	0.3147	0.885
0.3949	0.88	110	0.3424	0.855
0.3056	0.92	115	0.3620	0.835
0.4219	0.96	120	0.3437	0.855
0.3343	1.0	125	0.3257	0.865

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cpu
Datasets 2.21.0
Tokenizers 0.19.1