Metadata polish: co2_eq_emissions block, carbon-emissions+codecarbon tags, fix license typo, CodeCarbon citation

README.md

@@ -1,23 +1,35 @@
 ---
 base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
-datasets: joshuasundance/mypo-4k-rfc
+datasets:
+- joshuasundance/mypo-4k-rfc
+language:
+- en
+- code
 library_name: peft
+license: apache-2.0
 pipeline_tag: text-generation
 model_name: mypo-qwen2.5-coder-1.5b-dpo-v2
 tags:
 - generated_from_trainer
 - dpo
-- hf_jobs
+- trl
+- preference-optimization
 - lora
 - peft
 - python
-- qwen2.5-coder
-- code
 - type-hints
+- code
+- qwen2.5-coder
 - mypo
-- trl
-- preference-optimization
-licence: license
+- hf_jobs
+- codecarbon
+- carbon-emissions
+co2_eq_emissions:
+  emissions: 238.0
+  source: "CodeCarbon v3.2.6 (measured)"
+  training_type: "fine-tuning"
+  geographical_location: "Virginia, USA (AWS us-east-1)"
+  hardware_used: "1 x NVIDIA A10G (HF Jobs a10g-large)"
 ---
 
 # Model Card for mypo-qwen2.5-coder-1.5b-dpo-v2
@@ -128,8 +140,28 @@ CodeCarbon telemetry from the training run (`emissions.csv` in this repo):
 
 - TRL 1.2.0, Transformers 5.5.4, PyTorch 2.11.0, Datasets 4.8.4, Tokenizers 0.22.2, PEFT ≥ 0.12, bitsandbytes ≥ 0.44.
 
+## License
+
+Apache 2.0 (inherits from the [Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) base model).
+
 ## Citations
 
+### CodeCarbon (emissions tracking)
+
+Emissions for this run were measured with [CodeCarbon](https://codecarbon.io/) v3.2.6.
+
+```bibtex
+@software{codecarbon,
+  author  = {Benoit Courty and Victor Schmidt and Sasha Luccioni and Goyal-Kamal and MarionCoutarel and Boris Feld and Jérémy Lecourt and LiamConnell and Amine Saboni and Inimaz and supatomic and Mathilde Léval and Luis Blanche and Alexis Cruveiller and Ouminasara and Franklin Zhao and Aditya Joshi and Alexis Bogroff and Hugues de Lavoreille and Niko Laskaris and Edoardo Abati and Douglas Blank and Ziyao Wang and Armin Catovic and Marc Alencon and Michał Stęchły and Christian Bauer and Lucas Otávio N. de Araújo and JPW and MinervaBooks},
+  title   = {{CodeCarbon: Estimate and track carbon emissions from machine learning computing}},
+  year    = 2024,
+  doi     = {10.5281/zenodo.11171501},
+  url     = {https://github.com/mlco2/codecarbon}
+}
+```
+
+### DPO
+
 ```bibtex
 @inproceedings{rafailov2023direct,
     title        = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
@@ -137,12 +169,16 @@ CodeCarbon telemetry from the training run (`emissions.csv` in this repo):
     year         = 2023,
     booktitle    = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023}
 }
+```
 
+### TRL
+
+```bibtex
 @software{vonwerra2020trl,
-  title   = {{TRL: Transformers Reinforcement Learning}},
+  title   = {{TRL: Transformer Reinforcement Learning}},
   author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
   license = {Apache-2.0},
   url     = {https://github.com/huggingface/trl},
-  year    = {2020}
+  year    = 2020
 }
 ```