metadata
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
model-index:
- name: scibert_scivocab_uncased-finetuned-mol-mlm-0.3
results: []
scibert_scivocab_uncased-finetuned-mol-mlm-0.3
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5049
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8725 | 1.0 | 180 | 0.6730 |
| 0.6668 | 2.0 | 360 | 0.6203 |
| 0.6078 | 3.0 | 540 | 0.5739 |
| 0.5656 | 4.0 | 720 | 0.5537 |
| 0.5385 | 5.0 | 900 | 0.5483 |
| 0.5163 | 6.0 | 1080 | 0.5335 |
| 0.5043 | 7.0 | 1260 | 0.5350 |
| 0.4927 | 8.0 | 1440 | 0.5173 |
| 0.4841 | 9.0 | 1620 | 0.5093 |
| 0.4765 | 10.0 | 1800 | 0.5058 |
| 0.4709 | 11.0 | 1980 | 0.5104 |
| 0.4673 | 12.0 | 2160 | 0.5017 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0