---
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: learn2therm
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# learn2therm

This model is a fine-tuned version of [Rostlab/prot_bert](https://huggingface.co/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