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

Loss: 1.5083

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: 2
total_train_batch_size: 4
total_eval_batch_size: 2
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
1.4885	0.1501	500	1.5464
1.5514	0.3001	1000	1.5525
1.622	0.4502	1500	1.5406
1.6887	0.6002	2000	1.5267
1.7604	0.7503	2500	1.5132
1.3489	0.9004	3000	1.5084

Framework versions

Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.0.0
Tokenizers 0.22.1

Mayank6255/qwen-1_5b-sft-eng

qwen-1_5b-sft-eng

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mayank6255/
qwen-1_5b-sft-eng