This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the llama-duo/synth_closed_qa_dataset_dedup dataset. It achieves the following results on the evaluation set:

Loss: 1.7580

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: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 128
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
0.7127	1.0	146	1.7010
0.6581	2.0	292	1.6853
0.6323	3.0	438	1.6891
0.6067	4.0	584	1.7035
0.591	5.0	730	1.7226
0.5752	6.0	876	1.7259
0.5603	7.0	1022	1.7422
0.5632	8.0	1168	1.7483
0.5497	9.0	1314	1.7570
0.5353	10.0	1460	1.7580

Framework versions

PEFT 0.12.0
Transformers 4.44.0
Pytorch 2.2.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

llama-duo/mistral_7b_0_3-closedqa-gpt4o-100k

mistral_7b_0_3-closedqa-gpt4o-100k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

llama-duo/
mistral_7b_0_3-closedqa-gpt4o-100k