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T5-3B-ch – AI Model by EGannod | AlphaNeural AI
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EGannod
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T5-3B-ch
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peft
tensorboard
safetensors
adapter
lora
transformers
google-t5/t5-3b
apache-2.0
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T5-3B-ch
This model is a fine-tuned version of
google-t5/t5-3b
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4411
Bleu: 0.2953
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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use 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: 10
Training results
Training Loss
Epoch
Step
Validation Loss
Bleu
0.5699
2.3258
1000
0.5428
0.1328
0.5037
4.6515
2000
0.4777
0.3525
0.476
6.9773
3000
0.4515
0.1759
0.4616
9.3025
4000
0.4411
0.2953
Framework versions
PEFT 0.18.0
Transformers 4.57.2
Pytorch 2.9.1+cu128
Datasets 4.4.1
Tokenizers 0.22.1
