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Farisya/
ft-poc

Name: ft-poc
Rating: 2.5 (11 reviews)

peft

tensorboard

safetensors

generated_from_trainer

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

adapter

apache-2.0

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ft-poc

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5077

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
3.6207	0.91	5	2.8472
2.1794	2.0	11	1.9461
1.8396	2.91	16	1.4070
1.0288	4.0	22	0.8795
0.7943	4.91	27	0.6335
0.5105	6.0	33	0.5606
0.5624	6.91	38	0.5307
0.4441	8.0	44	0.5145
0.5156	8.91	49	0.5080
0.2438	9.09	50	0.5077

Framework versions

PEFT 0.10.0
Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2

Farisya/ft-poc

ft-poc

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Farisya/
ft-poc