llama3_darulm_20_05_24_part1-2_128000_bpe_full_lr2e4_bs256 – AI Model by RefalMachine | AlphaNeural AI

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RefalMachine/
llama3_darulm_20_05_24_part1-2_128000_bpe_full_lr2e4_bs256

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text-generation

generated_from_trainer

RefalMachine/llama3_darulm_20_05_24_part1-2_128000_bpe_mean_init_03_07_24

autotrain_compatible

text-generation-inference

endpoints_compatible

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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