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train-bioR-concat-gen4 – AI Model by KrisMinchev | AlphaNeural AI
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train-bioR-concat-gen4
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transformers
safetensors
gpt_neox
text-generation
generated_from_trainer
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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train-bioR-concat-gen4
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.5219
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: 0.001
train_batch_size: 12
eval_batch_size: 12
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 96
total_eval_batch_size: 96
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
training_steps: 41972
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.7002
0.2382
10000
1.6141
0.6777
0.4765
20000
1.5702
0.6585
0.7147
30000
1.5310
0.6584
0.9530
40000
1.5219
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
