BioMedRoBERTa-finetuned-ner-pablo-just-classifier – AI Model by pabRomero | AlphaNeural AI

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pabRomero/
BioMedRoBERTa-finetuned-ner-pablo-just-classifier

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token-classification

generated_from_trainer

emilyalsentzer/Bio_ClinicalBERT

autotrain_compatible

endpoints_compatible

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BioMedRoBERTa-finetuned-ner-pablo-just-classifier

This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1228
Precision: 0.6701
Recall: 0.6809
F1: 0.6754
Accuracy: 0.9657

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: 0.01
train_batch_size: 512
eval_batch_size: 512
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 2048
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_ratio: 0.05
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.9697	16	0.2938	0.4425	0.5130	0.4751	0.9361
No log	2.0	33	0.1815	0.5546	0.5873	0.5705	0.9535
No log	2.9697	49	0.1617	0.5838	0.6189	0.6008	0.9575
No log	4.0	66	0.1482	0.6070	0.6396	0.6229	0.9602
No log	4.9697	82	0.1340	0.6465	0.6563	0.6513	0.9633
No log	6.0	99	0.1306	0.6561	0.6638	0.6599	0.9641
No log	6.9697	115	0.1290	0.6569	0.6705	0.6636	0.9645
No log	8.0	132	0.1246	0.6664	0.6794	0.6728	0.9654
No log	8.9697	148	0.1230	0.6699	0.6793	0.6745	0.9656
No log	9.6970	160	0.1228	0.6701	0.6809	0.6754	0.9657

Framework versions

Transformers 4.44.1
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1