A full fine-tune of unsloth/gemma-3-270m-it on the kth8/docker-compose-20000x dataset.
Usage example
System prompt
You are a helpful assistant.
User prompt
Show me the docker-compose.yml for this command: docker container run --name fba_blue-chip --cpuset-cpus 3,3 --workdir /home/proconsulates/sandor --log-driver gelf --log-opt gelf-address=udp://localhost:53559 --blkio-weight-device /dev/sdg8:439 ghcr.io/asparagine/gesturing:nightly --warn --full --read-only
Model Details
- Base Model:
unsloth/gemma-3-270m-it - Parameter Count: 268098176
- Training Method: Full Fine-Tune (FFT) - All parameters updated.
- Precision: torch.bfloat16
Training stats
- global_step: 2307
- training_loss: 0.03397511645447863
- train_runtime: 6456.2772
- train_samples_per_second: 2.858
- train_steps_per_second: 0.357
- total_flos: 3357685821331968.0
- epoch: 1.0
Hardware
- GPU: NVIDIA L4
Framework versions
- Unsloth: 2026.3.4
- TRL: 0.22.2
- Transformers: 4.56.2
- Pytorch: 2.10.0+cu128
- Datasets: 4.3.0
- Tokenizers: 0.22.2
License
This model is released under the Gemma license. See the Gemma Terms of Use for details.
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