metadata

base_model: MMG/mlm-spanish-roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: roberta-finetuned-intention-prediction-es
    results: []

roberta-finetuned-intention-prediction-es

This model is a fine-tuned version of MMG/mlm-spanish-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.9097
Accuracy: 0.6918
Precision: 0.6953
Recall: 0.6918
F1: 0.6848

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: 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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
2.2985	1.0	102	1.7435	0.4970	0.4378	0.4970	0.4215
1.3399	2.0	204	1.4205	0.5828	0.5872	0.5828	0.5624
0.8893	3.0	306	1.2699	0.6393	0.6276	0.6393	0.6192
0.5691	4.0	408	1.3327	0.6515	0.6604	0.6515	0.6417
0.3837	5.0	510	1.3836	0.6592	0.6710	0.6592	0.6528
0.2543	6.0	612	1.4253	0.6641	0.6703	0.6641	0.6528
0.1669	7.0	714	1.5317	0.6650	0.6795	0.6650	0.6546
0.1139	8.0	816	1.5939	0.6725	0.6754	0.6725	0.6615
0.0805	9.0	918	1.6987	0.6594	0.6696	0.6594	0.6518
0.0578	10.0	1020	1.6960	0.6793	0.6782	0.6793	0.6690
0.0374	11.0	1122	1.7590	0.6824	0.6877	0.6824	0.6729
0.03	12.0	1224	1.7425	0.6842	0.6859	0.6842	0.6785
0.0183	13.0	1326	1.8165	0.6830	0.6846	0.6830	0.6774
0.0152	14.0	1428	1.8348	0.6866	0.6927	0.6866	0.6799
0.0109	15.0	1530	1.8562	0.6940	0.6967	0.6940	0.6855
0.0097	16.0	1632	1.8766	0.6889	0.6947	0.6889	0.6833
0.0073	17.0	1734	1.8745	0.6920	0.6948	0.6920	0.6851
0.0062	18.0	1836	1.8944	0.6895	0.6919	0.6895	0.6825
0.0057	19.0	1938	1.9103	0.6936	0.6984	0.6936	0.6867
0.0052	20.0	2040	1.9097	0.6918	0.6953	0.6918	0.6848

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0