Model Card for AICrossSim/clm-200m

A 200M parameter language model trained on 22 * 200M tokens from FineWeb-Edu dataset.

Model Details

aixsim-200M is a transformer-based language model with approximately 200 million parameters (embedding layer params excluded). It uses RMSNorm for normalization and is trained on the FineWeb-Edu dataset.

• Developed by: AICrossSim
• Funded by: ARIA
• Model type: Transformer Language Model
• Language(s) (NLP): English
• Tokenizer: HuggingFaceTB/cosmo2-tokenizer
• Repository: AICrossSim/NewComputeBench

Training Details

Experiment setup and training logs can be found at wandb run.

Usage

import transformers

model_name="AICrossSim/clm-200m"
model = transformers.AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

lm-evaluation-harness

Tasks	Version	Filter	n-shot	Metric		Value		Stderr
wikitext	2	none	0	bits_per_byte	↓	1.0994	±	N/A
		none	0	byte_perplexity	↓	2.1427	±	N/A
		none	0	word_perplexity	↓	58.8531	±	N/A