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ModelHub XC 4ff5fc63f9 初始化项目,由ModelHub XC社区提供模型
Model: laion/nemosci-tasrep-a1mfc-dev1-maxeps__Qwen3-8B
Source: Original Platform
2026-04-21 18:37:54 +08:00

2.2 KiB

library_name, license, base_model, tags, model-index
library_name license base_model tags model-index
transformers other Qwen/Qwen3-8B
llama-factory
full
generated_from_trainer
name results
nemosci-tasrep-a1mfc-dev1-maxeps__Qwen3-8B

nemosci-tasrep-a1mfc-dev1-maxeps__Qwen3-8B

This model is a fine-tuned version of Qwen/Qwen3-8B on the /e/data1/datasets/playground/ot-baf/hf_hub/datasets--laion--nemotron-terminal-scientific_computing/snapshots/610c7db0b8510b87e3c99b3bd49660bc56821866_thinking_preprocessed, the /e/data1/datasets/playground/ot-baf/hf_hub/datasets--DCAgent--exp_tas_repetition_penalty_1.05_traces/snapshots/b4f5500e00651d5ffc7f8701f8a055d9b2b68a0a_thinking_preprocessed, the /e/data1/datasets/playground/ot-baf/hf_hub/datasets--DCAgent--a1_multifile_composition/snapshots/a19e5e467f3e83605b4de72bb5b7923e5e55efa9_thinking_preprocessed, the /e/data1/datasets/playground/ot-baf/hf_hub/datasets--DCAgent--exp_tas_max_episodes_512_traces/snapshots/236c1dc9aa6d24cf77ce281b5342d93bae685832_thinking_preprocessed and the /e/data1/datasets/playground/ot-baf/hf_hub/datasets--DCAgent--dev_set_part1_10k_glm_4.7_traces_jupiter/snapshots/f1871d1c1446b3b43cbfe2737d0df56cecf3f420_thinking_preprocessed datasets.

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: 4e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 32
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 96
  • total_eval_batch_size: 256
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) 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 4.57.6
  • Pytorch 2.9.1+cu130
  • Datasets 4.7.0
  • Tokenizers 0.22.2