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prot_bert-finetuned-tchard – AI Model by yiminghuang47 | AlphaNeural AI
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prot_bert-finetuned-tchard
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transformers
pytorch
tensorboard
bert
fill-mask
generated_from_trainer
autotrain_compatible
endpoints_compatible
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prot_bert-finetuned-tchard
This model is a fine-tuned version of
Rostlab/prot_bert
on the TChard dataset. It achieves the following results on the evaluation set:
Loss: 0.7164
Perplexity: 2.05
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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
1140
0.7619
0.8072
2.0
2280
0.7394
0.7385
3.0
3420
0.7315
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
