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Veggissss/
norallm_normistral-7b-warm-instruct_4bit_quant

Name: norallm_normistral-7b-warm-instruct_4bit_quant
Availability: InStock

peft

safetensors

generated_from_trainer

norallm/normistral-7b-warm-instruct

adapter

apache-2.0

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norallm_normistral-7b-warm-instruct_4bit_quant

This model is a fine-tuned version of norallm/normistral-7b-warm-instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0707

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: 0.0005
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.7	0.1954	100	0.5815
0.371	0.3907	200	0.3392
0.2114	0.5861	300	0.2257
0.1371	0.7814	400	0.1624
0.1141	0.9768	500	0.1242
0.0852	1.1719	600	0.1016
0.0756	1.3673	700	0.0852
0.0586	1.5626	800	0.0758
0.0525	1.7580	900	0.0707

Framework versions

PEFT 0.15.2
Transformers 4.51.3
Pytorch 2.7.0+cu118
Datasets 3.5.1
Tokenizers 0.21.1

Veggissss/norallm_normistral-7b-warm-instruct_4bit_quant

norallm_normistral-7b-warm-instruct_4bit_quant

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Veggissss/
norallm_normistral-7b-warm-instruct_4bit_quant