This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the aya_eng_hin_deu_train dataset. It achieves the following results on the evaluation set:

Loss: 1.3972

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
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
1.3844	0.2001	500	1.5404
1.4718	0.4002	1000	1.4760
1.3534	0.6002	1500	1.4330
1.2707	0.8003	2000	1.4054

Framework versions

Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.0.0
Tokenizers 0.22.1

Mayank6255/qwen-sft-eng-hin-deu

qwen-sft-eng-hin-deu

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mayank6255/
qwen-sft-eng-hin-deu