metadata
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: patentClassfication2
results: []
patentClassfication2
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: 0.6359
- Accuracy: 0.655
- F1: 0.6955
- Precision: 0.6304
- Recall: 0.7756
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: 1.939963376695812e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6809 | 1.0 | 500 | 0.6729 | 0.625 | 0.5541 | 0.6997 | 0.4587 |
| 0.6004 | 2.0 | 1000 | 0.6359 | 0.655 | 0.6955 | 0.6304 | 0.7756 |
| 0.4696 | 3.0 | 1500 | 0.6658 | 0.675 | 0.6919 | 0.6673 | 0.7185 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3