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: 0.6121
- Accuracy: 0.6746
- F1: 0.6765
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: 2.54241e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 41
- 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: 24
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6169 | 1.0 | 4438 | 0.6919 | 0.6121 | 0.6906 |
| 0.5475 | 2.0 | 8876 | 0.6121 | 0.6746 | 0.6765 |
| 0.4521 | 3.0 | 13314 | 0.7167 | 0.6706 | 0.6827 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for eclec/patentClassfication2
Base model
allenai/scibert_scivocab_uncased