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Mistral-LoRA-Hate-Target-Detection-new – AI Model by christinacdl | AlphaNeural AI
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Mistral-LoRA-Hate-Target-Detection-new
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peft
safetensors
generated_from_trainer
mistralai/Mistral-7B-v0.1
adapter
apache-2.0
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Mistral-LoRA-Hate-Target-Detection-new
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: 0.7969
Micro F1: 0.8409
Macro F1: 0.6542
Accuracy: 0.8409
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
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 6
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:
quant_method: QuantizationMethod.BITS_AND_BYTES
load_in_8bit: False
load_in_4bit: True
llm_int8_threshold: 6.0
llm_int8_skip_modules: None
llm_int8_enable_fp32_cpu_offload: False
llm_int8_has_fp16_weight: False
bnb_4bit_quant_type: nf4
bnb_4bit_use_double_quant: False
bnb_4bit_compute_dtype: float16
Framework versions
PEFT 0.6.2
