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scibert_scivocab_chembl_passages_v1 – AI Model by bitshott | AlphaNeural AI
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scibert_scivocab_chembl_passages_v1
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peft
safetensors
bert
fill-mask
adapter
lora
transformers
allenai/scibert_scivocab_uncased
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scibert_scivocab_chembl_passages_v1
This model is a fine-tuned version of
allenai/scibert_scivocab_uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5940
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: 5e-05
train_batch_size: 96
eval_batch_size: 96
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 192
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.7674
1.0
10209
0.6706
0.6936
2.0
20418
0.6131
0.6774
3.0
30627
0.5940
Framework versions
PEFT 0.17.1
Transformers 4.56.2
Pytorch 2.8.0+cu128
Datasets 4.1.1
Tokenizers 0.22.1
