davidramos/flan-t5-small-generation-code-documentation-50k-data

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flan-t5-small-generation-code-documentation-50k-data

This model is a fine-tuned version of google/flan-t5-small on the None dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

The following bitsandbytes quantization config was used during training:

• —loadin8bit: True
• —loadin4bit: False
• —llmint8threshold: 6.0
• —llmint8skip_modules: None
• —llmint8enablefp32cpu_offload: False
• —llmint8hasfp16weight: False
• —bnb4bitquant_type: fp4
• —bnb4bitusedoublequant: False
• —bnb4bitcompute_dtype: float32

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0002
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.03
• —num_epochs: 2

Training results

Framework versions

• —PEFT 0.6.0.dev0
• —Transformers 4.30.0
• —Pytorch 2.0.0
• —Datasets 2.14.5
• —Tokenizers 0.13.3