metadata

base_model: allenai/scibert_scivocab_uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: patentClassfication3
    results: []

patentClassfication3

This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5828
Accuracy: 0.6901

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: 2.51444e-05
train_batch_size: 8
eval_batch_size: 8
seed: 61
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 240
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6511	1.0	554	0.6841	0.6125
0.5721	2.0	1108	0.5828	0.6901

Framework versions

Transformers 4.31.0
Pytorch 2.0.0
Datasets 2.14.4
Tokenizers 0.13.3