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roberta-reman – AI Model by gustavecortal | AlphaNeural AI
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roberta-reman
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transformers
pytorch
roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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Model card
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cold_reman_gpu_v1
This model is a fine-tuned version of
ibm/ColD-Fusion
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4520
F1: 0.6592
Roc Auc: 0.7559
Recall: 0.6197
Precision: 0.704
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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Roc Auc
Recall
Precision
No log
1.0
452
0.4556
0.6
0.7160
0.5282
0.6944
0.4832
2.0
904
0.4520
0.6592
0.7559
0.6197
0.704
0.3505
3.0
1356
0.4658
0.6543
0.7530
0.6197
0.6929
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2
