llama3_darulm_20_05_24_part1-2_128000_bpe_full_lr2e4_bs256

This model is a fine-tuned version of RefalMachine/llama3_darulm_20_05_24_part1-2_128000_bpe_mean_init_03_07_24 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.3015
• Accuracy: 0.5256

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: 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
2.6896	0.05	2000	2.4747	0.5036
2.627	0.1	4000	2.4208	0.5091
2.5808	0.14	6000	2.3954	0.5122
2.5783	0.19	8000	2.3773	0.5148
2.5749	0.24	10000	2.3623	0.5165
2.5491	0.29	12000	2.3518	0.5183
2.526	0.34	14000	2.3425	0.5192
2.5316	0.38	16000	2.3346	0.5203
2.5107	0.43	18000	2.3266	0.5218
2.5155	0.48	20000	2.3210	0.5225
2.5063	0.53	22000	2.3153	0.5237
2.493	0.57	24000	2.3102	0.5242
2.5019	0.62	26000	2.3072	0.5247
2.5044	0.67	28000	2.3048	0.5250
2.4799	0.72	30000	2.3033	0.5254
2.4993	0.77	32000	2.3023	0.5255
2.5174	0.81	34000	2.3018	0.5256
2.4938	0.86	36000	2.3016	0.5256
2.5055	0.91	38000	2.3015	0.5256
2.5061	0.96	40000	2.3015	0.5256

Framework versions

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