synthetic-70-vsfc-xlm-r – AI Model by toreleon | AlphaNeural AI

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toreleon/
synthetic-70-vsfc-xlm-r

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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synthetic-70-vsfc-xlm-r

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

Loss: 1.7726
Precision: 0.8498
Recall: 0.4018
F1 Weighted: 0.5020
F1 Macro: 0.3865

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: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1 Weighted	F1 Macro
1.1007	0.22	25	1.1227	0.0021	0.0461	0.0041	0.0294
0.8388	0.45	50	0.7289	0.8086	0.8105	0.8075	0.6172
0.5915	0.67	75	1.0029	0.8601	0.5155	0.6026	0.4582
0.4876	0.89	100	1.5117	0.8650	0.4820	0.5787	0.4426
0.3964	1.12	125	1.3913	0.8461	0.3973	0.4908	0.3829
0.4464	1.34	150	1.3103	0.8332	0.5130	0.5554	0.4201
0.485	1.56	175	1.5958	0.8831	0.4277	0.5336	0.4108
0.4471	1.79	200	1.5570	0.8774	0.4713	0.5527	0.4252
0.3867	2.01	225	1.7726	0.8498	0.4018	0.5020	0.3865

Framework versions

Transformers 4.27.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2