metadata
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: learn2therm
results: []
learn2therm
This model is a fine-tuned version of Rostlab/prot_bert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6942
- F1: 0.0
- Accuracy: 0.5125
- Matthew: -0.0308
- Cfm: [1025, 2, 973, 0]
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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 25
- total_train_batch_size: 1600
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.26.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3