final-ft__roberta-clinical-wl-es__70k-ultrasounds – AI Model by manucos | AlphaNeural AI

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final-ftroberta-clinical-wl-es70k-ultrasounds

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plncmm/roberta-clinical-wl-es

autotrain_compatible

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final-ftroberta-clinical-wl-es70k-ultrasounds

This model is a fine-tuned version of plncmm/roberta-clinical-wl-es on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6177

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.9967	229	0.9228
No log	1.9978	459	0.8047
No log	2.9989	689	0.7665
0.958	4.0	919	0.7180
0.958	4.9967	1148	0.7044
0.958	5.9978	1378	0.6875
0.958	6.9989	1608	0.6674
0.7197	8.0	1838	0.6454
0.7197	8.9967	2067	0.6485
0.7197	9.9978	2297	0.6411
0.7197	10.9989	2527	0.6292
0.665	12.0	2757	0.6223
0.665	12.9967	2986	0.6311
0.665	13.9978	3216	0.6128
0.665	14.9989	3446	0.6141
0.6398	16.0	3676	0.6028
0.6398	16.9967	3905	0.6064
0.6398	17.9978	4135	0.6148
0.6398	18.9989	4365	0.6032
0.6398	19.9347	4580	0.6177

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1