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esm2_t12_35M_UR50D-finetuned-motif-prediction – AI Model by franzdietzmeyer | AlphaNeural AI
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esm2_t12_35M_UR50D-finetuned-motif-prediction
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transformers
safetensors
esm
token-classification
generated_from_trainer
facebook/esm2_t12_35M_UR50D
finetune
mit
autotrain_compatible
endpoints_compatible
us
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esm2_t12_35M_UR50D-finetuned-motif-prediction
This model is a fine-tuned version of
facebook/esm2_t12_35M_UR50D
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0180
Accuracy: 1.0000
F1: 1.0000
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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
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: 0.1
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.0912
1.0
97
0.0709
0.9917
0.9915
0.0234
2.0
194
0.0228
1.0000
1.0000
0.0174
3.0
291
0.0180
1.0000
1.0000
Framework versions
Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
