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Weni/
ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0

Name: ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0
Availability: InStock

generated_from_trainer

mistralai/Mistral-7B-Instruct-v0.2

adapter

apache-2.0

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ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0

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

Loss: 0.0503

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: 8
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.1409	0.06	100	0.0993
0.0916	0.12	200	0.0877
0.0965	0.19	300	0.0970
0.0933	0.25	400	0.0898
0.0776	0.31	500	0.0749
0.0793	0.37	600	0.0850
0.0768	0.43	700	0.0701
0.0597	0.5	800	0.0767
0.0648	0.56	900	0.0766
0.0635	0.62	1000	0.0649
0.0536	0.68	1100	0.0641
0.0511	0.74	1200	0.0559
0.0638	0.81	1300	0.0507
0.0462	0.87	1400	0.0512
0.0494	0.93	1500	0.0507
0.0457	0.99	1600	0.0503

Framework versions

PEFT 0.9.0
Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Weni/ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0

ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Weni/
ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0