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T5-fine_tuned_ – AI Model by AmitDantal | AlphaNeural AI
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AmitDantal
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T5-fine_tuned_
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peft
safetensors
adapter
lora
transformers
google-t5/t5-base
adapter
apache-2.0
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T5-fine_tuned_
This model is a fine-tuned version of
t5-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.9283
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
training_steps: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
5.8189
0.2
1000
2.7719
6.2095
0.4
2000
2.8892
6.2846
0.6
3000
2.9284
6.1986
0.8
4000
2.9283
6.2482
1.0
5000
2.9283
Framework versions
PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
