RefalMachine/ruadapt_qwen2.5_3B_ext_cl100k_bpe_32000_full_lr5e4_2k_bs256

ruadapt_qwen2.5_3B_ext_cl100k_bpe_32000_full_lr5e4_bs256

This model is a fine-tuned version of RefalMachine/ruadapt_qwen2.5_3B_ext_cl100k_bpe_32000_mean_init on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.2974
• Accuracy: 0.5218

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: 0.0005
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 64
• total_train_batch_size: 256
• total_eval_batch_size: 256
• optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.0	1	5.2631	0.3345
2.475	0.09	2000	2.3600	0.5135
2.4448	0.17	4000	2.3388	0.5160
2.4367	0.26	6000	2.3284	0.5172
2.4209	0.34	8000	2.3206	0.5185
2.4235	0.43	10000	2.3142	0.5194
2.4197	0.51	12000	2.3084	0.5201
2.421	0.6	14000	2.3037	0.5209
2.403	0.68	16000	2.3003	0.5214
2.4169	0.77	18000	2.2984	0.5217
2.414	0.85	20000	2.2977	0.5219
2.3972	0.94	22000	2.2974	0.5220

Framework versions

• Transformers 4.37.2
• Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
• Datasets 2.18.0
• Tokenizers 0.15.2