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justinwangx/
mistral-instruct-adv-robust-15-sft-lora

Name: mistral-instruct-adv-robust-15-sft-lora
Availability: InStock

tensorboard

safetensors

generated_from_trainer

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

finetune

apache-2.0

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mistral-instruct-adv-robust-15-sft-lora

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: 1.7347

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: 0.0003
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 16
total_train_batch_size: 256
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
3.1318	0.12	1	2.8353
3.1318	1.12	2	2.6364
3.1318	2.12	3	2.4946
3.1318	3.12	4	2.5337
2.7387	4.12	5	2.3354
2.7387	5.12	6	2.2143
2.7387	6.12	7	2.1649
2.7387	7.12	8	2.1062
2.7387	8.12	9	2.0854
2.2698	9.12	10	2.0497
2.2698	10.12	11	1.9576
2.2698	11.12	12	1.8585
2.2698	12.12	13	1.7771
2.2698	13.12	14	1.7952
1.9483	14.12	15	1.7796

Framework versions

Transformers 4.35.0
Pytorch 2.1.0a0+32f93b1
Datasets 2.14.6
Tokenizers 0.14.1

justinwangx/mistral-instruct-adv-robust-15-sft-lora

mistral-instruct-adv-robust-15-sft-lora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

justinwangx/
mistral-instruct-adv-robust-15-sft-lora