This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the nthakur/multilingual-deita-10k-v0-sft-v0.1 dataset. It achieves the following results on the evaluation set:

Loss: 0.6604

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: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
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
0.8266	0.2861	200	0.6874
0.7478	0.5722	400	0.6693
0.7963	0.8584	600	0.6609

Framework versions

PEFT 0.7.1
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

nthakur/Mistral-7B-Instruct-v0.2-multilingual-deita-10k-v0-sft-v0.1

Mistral-7B-Instruct-v0.2-multilingual-deita-10k-v0-sft-v0.1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nthakur/
Mistral-7B-Instruct-v0.2-multilingual-deita-10k-v0-sft-v0.1