christinacdl/Mistral-PromptTuning-Hate-Target-Detection-replicate

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Mistral-PromptTuning-Hate-Target-Detection-replicate

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.9956
• —Micro F1: 0.7803
• —Macro F1: 0.5265
• —Accuracy: 0.7803

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0001
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: constant
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.36.1
• —Pytorch 2.1.0+cu121
• —Datasets 2.13.1
• —Tokenizers 0.15.0

Training procedure

The following bitsandbytes quantization config was used during training:

• —quantmethod: QuantizationMethod.BITSAND_BYTES
• —loadin8bit: False
• —loadin4bit: True
• —llmint8threshold: 6.0
• —llmint8skip_modules: None
• —llmint8enablefp32cpu_offload: False
• —llmint8hasfp16weight: False
• —bnb4bitquant_type: nf4
• —bnb4bitusedoublequant: False
• —bnb4bitcompute_dtype: float16

Framework versions

• —PEFT 0.6.2