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qwen3-8b-gsm8k-fromEn-n5000-seed42-lora-fr – AI Model by xummer | AlphaNeural AI
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qwen3-8b-gsm8k-fromEn-n5000-seed42-lora-fr
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fr
This model is a fine-tuned version of
Qwen/Qwen3-8B
on the gsm8k_fr_train dataset. It achieves the following results on the evaluation set:
Loss: 0.3580
Accuracy: 0.8953
Mcq Accuracy: 0.4003
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Mcq Accuracy
0.3467
0.64
200
0.3502
0.8936
0.3655
0.3162
1.2784
400
0.3438
0.8956
0.3909
0.2870
1.9184
600
0.3357
0.8977
0.3976
0.2410
2.5568
800
0.3587
0.8948
0.3936
Framework versions
PEFT 0.18.1
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
