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Sneka/
mistral-try-finetune

Name: mistral-try-finetune
Availability: InStock

safetensors

generated_from_trainer

mistralai/Mistral-7B-Instruct-v0.1

finetune

apache-2.0

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mistral-try-finetune

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3805

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: 2.5e-05
train_batch_size: 2
eval_batch_size: 8
seed: 18
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_steps: 5
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.5606	0.57	50	0.8581
0.5656	1.14	100	0.5153
0.3651	1.71	150	0.4257
0.2995	2.29	200	0.3750
0.2008	2.86	250	0.3405
0.1693	3.43	300	0.3282
0.144	4.0	350	0.3156
0.1112	4.57	400	0.3209
0.0949	5.14	450	0.3346
0.0801	5.71	500	0.3212
0.0717	6.29	550	0.3288
0.0579	6.86	600	0.3255
0.0486	7.43	650	0.3359
0.0495	8.0	700	0.3273
0.0374	8.57	750	0.3617
0.0377	9.14	800	0.3725
0.0324	9.71	850	0.3697
0.0338	10.29	900	0.3946
0.0305	10.86	950	0.3605
0.0289	11.43	1000	0.3805

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0

Sneka/mistral-try-finetune

mistral-try-finetune

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Sneka/
mistral-try-finetune