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test_TwoWayLoss_25K_bs64_P4_N1 – AI Model by bdpc | AlphaNeural AI
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test_TwoWayLoss_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_TwoWayLoss_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: 8.8668
Accuracy: 0.5430
Precision: 0.0114
Recall: 0.5359
F1: 0.0224
Hamming: 0.4570
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: 8
eval_batch_size: 8
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
8.9097
0.0
5
8.8974
0.5287
0.0107
0.5189
0.0210
0.4713
8.1387
0.0
10
8.8668
0.5430
0.0114
0.5359
0.0224
0.4570
Framework versions
Transformers 4.35.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.7.1
Tokenizers 0.14.1
