metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SMM-classifier-1
results: []
SMM-classifier-1
This model is a fine-tuned version of Kuaaangwen/bert-base-cased-finetuned-chemistry on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5506
- Accuracy: 0.8333
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 0.2044 | 0.8333 |
| No log | 2.0 | 14 | 0.3574 | 0.8333 |
| No log | 3.0 | 21 | 0.1551 | 0.8333 |
| No log | 4.0 | 28 | 0.9122 | 0.8333 |
| No log | 5.0 | 35 | 0.9043 | 0.8333 |
| No log | 6.0 | 42 | 0.7262 | 0.8333 |
| No log | 7.0 | 49 | 0.5977 | 0.8333 |
| No log | 8.0 | 56 | 0.5567 | 0.8333 |
| No log | 9.0 | 63 | 0.5484 | 0.8333 |
| No log | 10.0 | 70 | 0.5506 | 0.8333 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2