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--- |
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library_name: transformers |
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tags: |
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- language-model |
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license: odc-by |
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datasets: |
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- HuggingFaceFW/fineweb-edu |
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language: |
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- en |
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--- |
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# Model Card for AICrossSim/clm-200m |
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A 200M parameter language model trained on `22 * 200M` tokens from FineWeb-Edu dataset. |
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## Model Details |
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aixsim-200M is a transformer-based language model with approximately 200 million parameters (embedding layer params excluded). |
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It uses RMSNorm for normalization and is trained on the FineWeb-Edu dataset. |
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- **Developed by:** AICrossSim |
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- **Funded by:** [ARIA](https://www.aria.org.uk/) |
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- **Model type:** Transformer Language Model |
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- **Language(s) (NLP):** English |
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- **Tokenizer:** [HuggingFaceTB/cosmo2-tokenizer](https://huggingface.co/HuggingFaceTB/cosmo2-tokenizer) |
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- **Repository:** [AICrossSim/NewComputeBench](https://github.com/AICrossSim/NewComputeBench) |
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## Training Details |
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Experiment setup and training logs can be found at [wandb run](https://wandb.ai/cz98/torchtitan/runs/uhnlw6k8?nw=nwusercz98). |
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## Usage |
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```python |
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import transformers |
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model_name="AICrossSim/clm-200m" |
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model = transformers.AutoModelForCausalLM.from_pretrained(model_name) |
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tokenizer = transformers.AutoTokenizer.from_pretrained(model_name) |
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``` |
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## lm-evaluation-harness |
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| Tasks |Version|Filter|n-shot| Metric | | Value | |Stderr| |
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|--------|------:|------|-----:|---------------|---|------:|---|------| |
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|wikitext| 2|none | 0|bits_per_byte |↓ | 1.0994|± | N/A| |
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| | |none | 0|byte_perplexity|↓ | 2.1427|± | N/A| |
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| | |none | 0|word_perplexity|↓ |58.8531|± | N/A| |
