trained_model – AI Model by taronklm | AlphaNeural AI

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trained_model

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generated_from_trainer

Qwen/Qwen2.5-0.5B-Instruct

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trained_model

This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.5432
Bertscore Precision: 0.9305
Bertscore Recall: 0.9338
Bertscore F1: 0.9321

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: 0.0001
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Bertscore Precision	Bertscore Recall	Bertscore F1
No log	0.9664	18	1.1003	0.8802	0.8897	0.8849
1.7123	1.9866	37	0.6787	0.9207	0.9228	0.9218
1.7123	2.9530	55	0.5895	0.9300	0.9330	0.9315
0.5828	3.9732	74	0.5516	0.9330	0.9355	0.9342
0.4501	4.8322	90	0.5432	0.9305	0.9338	0.9321

Framework versions

PEFT 0.13.0
Transformers 4.45.1
Pytorch 2.5.1+cpu
Datasets 3.0.1
Tokenizers 0.20.0