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finetune_t5_base_only_hack – AI Model by rhythm00 | AlphaNeural AI
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finetune_t5_base_only_hack
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transformers
safetensors
t5
text2text-generation
generated_from_trainer
cointegrated/rut5-base-multitask
finetune
mit
text-generation-inference
endpoints_compatible
us
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finetune_t5_base_only_hack
This model is a fine-tuned version of
cointegrated/rut5-base-multitask
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.4584
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: 0.0004
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 8
Training results
Training Loss
Epoch
Step
Validation Loss
1.8215
3.86
150
1.5392
1.579
7.72
300
1.4584
Framework versions
Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0
