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ViT-BERT-Chess-V2 – AI Model by Migga | AlphaNeural AI
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Migga
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ViT-BERT-Chess-V2
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transformers
pytorch
vision-encoder-decoder
image-to-text
generated_from_trainer
endpoints_compatible
us
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ViT-BERT-Chess-V2
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 3.7128
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: 10
eval_batch_size: 4
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
4.0385
1.0
2770
3.9132
3.7453
2.0
5540
3.7552
3.6513
3.0
8310
3.7128
Framework versions
Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
