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us-patents-240918 – Dataset by jamieoliver | AlphaNeural AI
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us-patents-240918
This model is a fine-tuned version of
microsoft/deberta-v3-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0226
Pearson: 0.8316
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
See
https://github.com/jamieoliver/us-patents-240918
for training details.
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 8e-05
train_batch_size: 128
eval_batch_size: 256
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Pearson
No log
1.0
214
0.0298
0.7996
No log
2.0
428
0.0243
0.8201
0.0392
3.0
642
0.0223
0.8302
0.0392
4.0
856
0.0226
0.8316
Framework versions
Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0
