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Qwen3-4B-SFT-envbench_weave_2500 – AI Model by waleko | AlphaNeural AI
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Qwen3-4B-SFT-envbench_weave_2500
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transformers
safetensors
qwen3
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3-4B
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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Qwen3-4B-SFT-envbench_weave_2500
This model is a fine-tuned version of
Qwen/Qwen3-4B
on the envbench_weave_2500 dataset. It achieves the following results on the evaluation set:
Loss: 0.3336
Accuracy: 0.9056
Num Input Tokens Seen: 93658048
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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 16
optimizer: Use OptimizerNames.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_ratio: 0.1
num_epochs: 5.0
Training results
Framework versions
Transformers 4.52.4
Pytorch 2.6.0a0+df5bbc09d1.nv24.12
Datasets 3.6.0
Tokenizers 0.21.1
