mdt-ie-ner-baseline – AI Model by OSainz | AlphaNeural AI

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OSainz/
mdt-ie-ner-baseline

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token-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6486
Precision: 0.6540
Recall: 0.6944
F1: 0.6736

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
No log	1.0	38	0.7892	0.5800	0.6787	0.6255
No log	2.0	76	0.5906	0.7267	0.7540	0.7401
No log	3.0	114	0.5466	0.7219	0.7771	0.7485
No log	4.0	152	0.5249	0.7266	0.7623	0.7440
No log	5.0	190	0.5261	0.7228	0.7674	0.7445

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2