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distilbert_rand_20_v2_rte – AI Model by Hartunka | AlphaNeural AI
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Hartunka
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distilbert_rand_20_v2_rte
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
en
glue
Hartunka/distilbert_rand_20_v2
finetune
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autotrain_compatible
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distilbert_rand_20_v2_rte
This model is a fine-tuned version of
Hartunka/distilbert_rand_20_v2
on the GLUE RTE dataset. It achieves the following results on the evaluation set:
Loss: 0.6893
Accuracy: 0.5343
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: 5e-05
train_batch_size: 256
eval_batch_size: 256
seed: 10
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 50
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6973
1.0
10
0.6893
0.5343
0.6835
2.0
20
0.6986
0.5271
0.6373
3.0
30
0.7705
0.5126
0.5447
4.0
40
0.8775
0.4982
0.4205
5.0
50
1.0983
0.4801
0.2894
6.0
60
1.4305
0.5018
Framework versions
Transformers 4.50.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.21.1
