You can deploy this model and start earning money today!

vjvk/
Mistral-7B-Instruct-v0.2-GPTQ_finetune

Name: Mistral-7B-Instruct-v0.2-GPTQ_finetune
Availability: InStock

peft

safetensors

generated_from_trainer

TheBloke/Mistral-7B-Instruct-v0.2-GPTQ

adapter

apache-2.0

Views

No views yet

Mistral-7B-Instruct-v0.2-GPTQ_finetune

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.6337

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: 0.0002
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.2048	0.5714	1	1.8649
1.559	1.7143	3	1.7810
1.3635	2.8571	5	1.7115
1.3561	4.0	7	1.6645
2.7801	4.5714	8	1.6496
0.898	5.7143	10	1.6337

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

vjvk/Mistral-7B-Instruct-v0.2-GPTQ_finetune

Mistral-7B-Instruct-v0.2-GPTQ_finetune

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vjvk/
Mistral-7B-Instruct-v0.2-GPTQ_finetune