Model Card for AICrossSim/clm-60m

A 60M parameter language model trained on the FineWeb dataset.

Model Details

Model Description

aixsim-60M is a transformer-based language model with approximately 60 million parameters (embedding layer params excluded). It uses RMSNorm for normalization and is trained on the FineWeb dataset.

• Developed by: AICrossSim
• Funded by: ARIA
• Model type: Transformer Language Model
• Language(s) (NLP): English
• License: odc-by
• Tokenizer: Based on HuggingFaceTB/cosmo2-tokenizer

Model Sources

• Repository: https://github.com/AICrossSim/NewComputeBench

Training Details

Training Data

The model was trained 60*22M tokens from the FineWeb dataset (HuggingFaceTB/fineweb).

Training Procedure

Training Hyperparameters

• Batch Size: 48
• Sequence Length: 2048
• Learning Rate: 0.0001
• Optimizer: AdamW with fused=false
• Training Steps: 7075
• Warmup Steps: 1415
• Maximum Gradient Norm: 1.0
• Training regime: Mixed precision (bfloat16 for parameters, float32 for reduction)
• Data Parallel Configuration:
  • Shard Degree: 2
  • Replicate Degree: 1
• Random Seed: 42
• Garbage Collection Frequency: Every 50 steps
• Compilation: Enabled