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train-bioR-concat-gen5 – AI Model by KrisMinchev | AlphaNeural AI
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train-bioR-concat-gen5
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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-gen5
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.4270
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: 41949
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.7032
0.2384
10000
1.5264
0.68
0.4768
20000
1.4609
0.6677
0.7151
30000
1.4266
0.6487
0.9535
40000
1.4270
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
