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promptly-tuned – AI Model by RevLash | AlphaNeural AI
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RevLash
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promptly-tuned
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peft
tensorboard
safetensors
generated_from_trainer
Qwen/Qwen2.5-0.5B-Instruct
adapter
apache-2.0
us
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promptly-tuned
This model is a fine-tuned version of
Qwen/Qwen2.5-0.5B-Instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.3650
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: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
11.2538
1.0
7
1.4416
24.3241
2.0
14
1.3788
11.9827
3.0
21
1.3650
Framework versions
PEFT 0.14.0
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0
