cot_method2test-mistral-7B_v1 – AI Model by Minata | AlphaNeural AI

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Minata/
cot_method2test-mistral-7B_v1

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mistralai/Mistral-7B-v0.1

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cot_method2test-mistral-7B_v1

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

Loss: 0.7463

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: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 5
training_steps: 50

Training results

Training Loss	Epoch	Step	Validation Loss
1.0057	0.48	5	1.2410
0.9781	0.95	10	1.1410
0.8181	1.43	15	1.0440
0.7273	1.9	20	0.9502
0.6721	2.38	25	0.8735
0.5397	2.86	30	0.8148
0.4642	3.33	35	0.7771
0.4328	3.81	40	0.7565
0.3788	4.29	45	0.7490
0.4171	4.76	50	0.7463

Framework versions

PEFT 0.7.2.dev0
Transformers 4.37.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0