48 lines
1.6 KiB
Markdown
48 lines
1.6 KiB
Markdown
---
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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-60m
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A 60M parameter language model trained on `22 * 60M` tokens from FineWeb-Edu dataset.
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## Model Details
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aixsim-60M is a transformer-based language model with approximately 60 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/7kttp3qt?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-60m"
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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 |↓ | 1.6693|± | N/A|
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| | |none | 0|byte_perplexity|↓ | 3.1806|± | N/A|
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| | |none | 0|word_perplexity|↓ |486.5306|± | N/A| |