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MNLP_M3_rag_model – AI Model by artdev99 | AlphaNeural AI
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MNLP_M3_rag_model
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transformers
safetensors
qwen3
text-generation
generated_from_trainer
conversational
Qwen/Qwen3-0.6B-Base
finetune
apache-2.0
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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MNLP_M3_rag_model
This model is a fine-tuned version of
Qwen/Qwen3-0.6B-Base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4120
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 64
total_eval_batch_size: 64
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
0.4932
1.0
9996
0.4120
0.3206
2.0
19992
0.4237
Framework versions
Transformers 4.52.4
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.1
