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albert-base-v2-wordnet_dataset_two-fine-tuned – AI Model by Carick | AlphaNeural AI
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Carick
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albert-base-v2-wordnet_dataset_two-fine-tuned
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transformers
tensorboard
safetensors
albert
text-classification
generated_from_trainer
albert/albert-base-v2
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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albert-base-v2-wordnet_dataset_two-fine-tuned
This model is a fine-tuned version of
albert-base-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3013
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.4486
1.0
7938
0.4045
0.379
2.0
15876
0.3372
0.3267
3.0
23814
0.3013
Framework versions
Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0
