bihungba1101/essay-grammar-range-qwen3.5-4b-trl-completions
TRL Completion logs This dataset contains the completions generated during training using trl. Find the trained model at https://huggingface.co/bihungba1101/essay-grammar-range-qwen3.5-4b-grpo. The completions are stored in parquet files, and each file contains the completions for a single step of training (depending on the logging_steps argument). Each file contains the following columns: step: the step of training prompt: the prompt used to generate the completion completion:… See the full description on the dataset page: https://huggingface.co/datasets/bihungba1101/essay-grammar-range-qwen3.5-4b-trl-completions.
TRL Completion logs
This dataset contains the completions generated during training using trl.
Find the trained model at https://huggingface.co/bihungba1101/essay-grammar-range-qwen3.5-4b-grpo.
The completions are stored in parquet files, and each file contains the completions for a single step of training (depending on the logging_steps argument).
Each file contains the following columns:
step: the step of trainingprompt: the prompt used to generate the completioncompletion: the completion generated by the model<reward_function_name>: the reward(s) assigned to the completion by the reward function(s) used during trainingadvantage: the computed advantage for the completion
Having this data stored as a simple parquet file makes it easy to load and analyze using the Datasets Viewer, Polars, Pandas, etc.
You can load the dataset using the datasets library:
import datasets
dataset = datasets.load_dataset("bihungba1101/essay-grammar-range-qwen3.5-4b-trl-completions")You can also load the dataset using Polars:
import polars as pl
# Login using e.g. `hf auth login` to access this dataset if it's private
df = pl.read_parquet(f"hf://datasets/bihungba1101/essay-grammar-range-qwen3.5-4b-trl-completions/*.parquet")