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ViTay-TDA – AI Model by FiveC | AlphaNeural AI
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FiveC
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ViTay-TDA
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transformers
safetensors
mbart
text2text-generation
generated_from_trainer
FiveC/BartTay
finetune
mit
endpoints_compatible
us
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ViTay-TDA
This model is a fine-tuned version of
FiveC/BartTay
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1377
Sacrebleu: 25.7507
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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Sacrebleu
0.1358
1.0
6301
0.1450
21.6836
0.0955
2.0
12602
0.1363
24.9251
0.0776
3.0
18903
0.1377
25.7507
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
