README.md

metadata

library_name: transformers
base_model: pysentimiento/robertuito-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - recall
model-index:
  - name: test_trainer
    results: []

test_trainer

This model is a fine-tuned version of pysentimiento/robertuito-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0158
• F1: 0.9987
• Recall: 0.9987

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: 64
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Recall
No log	1.0	95	0.0224	0.9960	0.9960
No log	2.0	190	0.0103	0.9987	0.9987
No log	3.0	285	0.0109	0.9987	0.9987
No log	4.0	380	0.0198	0.9974	0.9973
No log	5.0	475	0.0130	0.9987	0.9987
0.0139	6.0	570	0.0130	0.9987	0.9987
0.0139	7.0	665	0.0131	0.9987	0.9987
0.0139	8.0	760	0.0133	0.9987	0.9987
0.0139	9.0	855	0.0134	0.9987	0.9987
0.0139	10.0	950	0.0136	0.9987	0.9987
0.0	11.0	1045	0.0137	0.9987	0.9987
0.0	12.0	1140	0.0138	0.9987	0.9987
0.0	13.0	1235	0.0138	0.9987	0.9987
0.0	14.0	1330	0.0140	0.9987	0.9987
0.0	15.0	1425	0.0141	0.9987	0.9987
0.0	16.0	1520	0.0142	0.9987	0.9987
0.0	17.0	1615	0.0143	0.9987	0.9987
0.0	18.0	1710	0.0144	0.9987	0.9987
0.0	19.0	1805	0.0145	0.9987	0.9987
0.0	20.0	1900	0.0146	0.9987	0.9987
0.0	21.0	1995	0.0147	0.9987	0.9987
0.0	22.0	2090	0.0147	0.9987	0.9987
0.0	23.0	2185	0.0148	0.9987	0.9987
0.0	24.0	2280	0.0149	0.9987	0.9987
0.0	25.0	2375	0.0150	0.9987	0.9987
0.0	26.0	2470	0.0151	0.9987	0.9987
0.0	27.0	2565	0.0151	0.9987	0.9987
0.0	28.0	2660	0.0152	0.9987	0.9987
0.0	29.0	2755	0.0152	0.9987	0.9987
0.0	30.0	2850	0.0153	0.9987	0.9987
0.0	31.0	2945	0.0153	0.9987	0.9987
0.0	32.0	3040	0.0154	0.9987	0.9987
0.0	33.0	3135	0.0155	0.9987	0.9987
0.0	34.0	3230	0.0154	0.9987	0.9987
0.0	35.0	3325	0.0154	0.9987	0.9987
0.0	36.0	3420	0.0155	0.9987	0.9987
0.0	37.0	3515	0.0155	0.9987	0.9987
0.0	38.0	3610	0.0156	0.9987	0.9987
0.0	39.0	3705	0.0156	0.9987	0.9987
0.0	40.0	3800	0.0156	0.9987	0.9987
0.0	41.0	3895	0.0155	0.9987	0.9987
0.0	42.0	3990	0.0156	0.9987	0.9987
0.0	43.0	4085	0.0156	0.9987	0.9987
0.0	44.0	4180	0.0156	0.9987	0.9987
0.0	45.0	4275	0.0157	0.9987	0.9987
0.0	46.0	4370	0.0157	0.9987	0.9987
0.0	47.0	4465	0.0157	0.9987	0.9987
0.0	48.0	4560	0.0158	0.9987	0.9987
0.0	49.0	4655	0.0158	0.9987	0.9987
0.0	50.0	4750	0.0158	0.9987	0.9987

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1