Apizhai/Albert-IT-JobRecommendation

This repository contains a Albert model designed for text classification. The architecture of the model is based on the Albert Base v2 model.

Library

pip install transformers
pip install sentencepiece

Example

from transformers import AutoModel,AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained('Apizhai/Albert-IT-JobRecommendation', use_fast=False),
model = AutoModel.from_pretrained('Apizhai/Albert-IT-JobRecommendation')

Training hyperparameters

The following hyperparameters were used during training:

• max_seq_length: 128
• max_length: 128
• train_batch_size: 4
• eval_batch_size: 32
• num_train_epochs: 10
• evaluate_during_training: False
• evaluate_during_training_steps: 100
• use_multiprocessing: False
• fp16: True
• save_steps: -1
• save_eval_checkpoints: False
• save_model_every_epoch: False
• no_cache: True
• reprocess_input_data: True
• overwrite_output_dir: True
• preprocess_inputs: False
• num_return_sequences: 1

Score

• f1-score: 0.85574
• macro avg: 0.84748
• weighted avg: 0.81575