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: 6.9495

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: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_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

Training results

Training Loss	Epoch	Step	Validation Loss
5.1634	0.9991	582	6.9495

Framework versions

Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0

klcsp/mistral-7b-0.3-gpt4o_100k_closedqa-fft

mistral-7b-0.3-gpt4o_100k_closedqa-fft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

klcsp/
mistral-7b-0.3-gpt4o_100k_closedqa-fft