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glaborie/
shawgpt-ft

Name: shawgpt-ft
Availability: InStock

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

apache-2.0

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shawgpt-ft

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: 1.4650

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: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
4.2259	1.0	4	3.7826
3.4714	2.0	8	3.1217
2.9082	3.0	12	2.6339
2.4457	4.0	16	2.2700
2.1686	5.0	20	1.9701
1.699	6.0	24	1.7254
1.4794	7.0	28	1.5955
1.4546	8.0	32	1.5156
1.3939	9.0	36	1.4769
1.2823	10.0	40	1.4650

Framework versions

PEFT 0.16.0
Transformers 4.53.2
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.2

glaborie/shawgpt-ft

shawgpt-ft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

glaborie/
shawgpt-ft