This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the aya_deu_train dataset. It achieves the following results on the evaluation set:

Loss: 1.5612

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: 1e-05
train_batch_size: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 8
total_eval_batch_size: 4
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
1.6751	0.3001	500	1.6416
1.7003	0.6002	1000	1.5897
1.3833	0.9004	1500	1.5618

Framework versions

Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.0.0
Tokenizers 0.22.1

Mayank6255/qwen-1_5b-sft-deu

qwen-1_5b-sft-deu

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mayank6255/
qwen-1_5b-sft-deu