🩵 Rain-100M — Model Card
Rain-100M is an experimental language model trained from scratch based on the Qwen3 architecture.
🧠 Training & Data
- Training corpus:
HuggingFaceFW/fineweb-edu - Total tokens: ~3B
- Language: English only
- Tokenizer: Newly trained 16k BPE (optimized for small/compact models)
- Max sequence length: 4096
Sample training metrics:
train/grad_norm: 0.6640625
train/learning_rate: 0.00000000002171853813
train/loss: 3.4459
🏗️ Architecture (Qwen3-style)
- Parameters: ~100M
- Layers: 12 Transformer layers
- Hidden size: 768
- Attention heads: 12
- MLP dimension: 2048
- Activation: SiLU
- Weight dtype: bfloat16
- RMSNorm eps: 1e-6
- RoPE θ: 10000
- Inference framework:
transformers
⚠️ Limitations
- Trained only on English data; weak or no capabilities in other languages, not suitable as a general-purpose chat model or for safety-critical use cases.
- No system-level alignment or safety fine-tuning has been applied.
📄 License
When using this model locally, please also comply with the licenses of the fineweb-edu dataset and the transformers / Qwen3-related components.
中文版本
🩵 Rain-100M — Model Card
Rain-100M 是一个基于 Qwen3 架构 从零训练的实验语言模型。
🧠 训练与数据
- 训练语料：HuggingFaceFW/fineweb-edu
- Tokens 数量：约 3B
- 语言：仅英语
- Tokenizer：全新训练的 16k BPE（面向轻量模型优化）
- 最大序列长度：4096
训练参数：
train/grad_norm:0.6640625
train/learning_rate:0.00000000002171853813
train/loss:3.4459
🏗️ 模型结构（Qwen3 规格）
- 参数量：约 100M
- 层数：12 层 Transformer
- 隐藏维度：768
- 注意力头数：12
- 中间层维度：2048
- 激活函数：SiLU
- 权重类型：bfloat16
- RMSNorm eps：1e-6
- RoPE θ：10000
- 推理框架：transformers
⚠️ 限制
- 仅使用英文语料，小语言能力有限，不适合作为通用聊天或安全敏感任务；
- 无系统对齐与安全强化。
📄 License
请在本地使用时遵循 fineweb-edu 数据集与 transformers/Qwen3 相关许可证。
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