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ruadapt_qwen2.5_3B_darulm_bpe_64000_full_lr3e4_bs256 – AI Model by RefalMachine | AlphaNeural AI
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RefalMachine
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ruadapt_qwen2.5_3B_darulm_bpe_64000_full_lr3e4_bs256
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tensorboard
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qwen2
generated_from_trainer
RefalMachine/ruadapt_qwen2.5_3B_darulm_bpe_64000_mean_init
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ruadapt_qwen2.5_3B_darulm_bpe_64000_full_lr3e4_bs256
This model is a fine-tuned version of
RefalMachine/ruadapt_qwen2.5_3B_darulm_bpe_64000_mean_init
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.5169
Accuracy: 0.4977
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: 0.0003
train_batch_size: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 64
gradient_accumulation_steps: 2
total_train_batch_size: 256
total_eval_batch_size: 128
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
6.3928
0.1604
2.7011
0.18
2000
2.5622
0.4925
2.673
0.35
4000
2.5308
0.4960
2.6503
0.53
6000
2.5210
0.4971
2.6557
0.7
8000
2.5176
0.4977
2.6422
0.88
10000
2.5169
0.4976
Framework versions
Transformers 4.37.2
Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
Datasets 2.18.0
Tokenizers 0.15.2
