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test_AsymmetricLoss_25K_bs64_P4_N1 – AI Model by bdpc | AlphaNeural AI
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test_AsymmetricLoss_25K_bs64_P4_N1
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transformers
pytorch
bert
text-classification
generated_from_trainer
allenai/scibert_scivocab_uncased
finetune
autotrain_compatible
endpoints_compatible
us
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test_AsymmetricLoss_25K_bs64_P4_N1
This model is a fine-tuned version of
allenai/scibert_scivocab_uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6203
Accuracy: 0.7448
Precision: 0.0101
Recall: 0.2592
F1: 0.0194
Hamming: 0.2552
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: 40
eval_batch_size: 40
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 10
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
Hamming
0.6901
0.0
5
0.6457
0.6626
0.0099
0.3394
0.0192
0.3374
0.6344
0.0
10
0.6203
0.7448
0.0101
0.2592
0.0194
0.2552
Framework versions
Transformers 4.35.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.7.1
Tokenizers 0.14.1
