| | --- |
| | base_model: allenai/scibert_scivocab_cased |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: SOMD-scibert-stage2-v1 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # SOMD-scibert-stage2-v1 |
| |
|
| | This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0115 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | No log | 1.0 | 202 | 0.4607 | |
| | | No log | 1.99 | 404 | 0.2408 | |
| | | 0.5891 | 2.99 | 606 | 0.1086 | |
| | | 0.5891 | 3.98 | 808 | 0.0879 | |
| | | 0.1352 | 4.98 | 1010 | 0.0505 | |
| | | 0.1352 | 5.97 | 1212 | 0.0286 | |
| | | 0.1352 | 6.97 | 1414 | 0.0262 | |
| | | 0.0541 | 7.96 | 1616 | 0.0231 | |
| | | 0.0541 | 8.96 | 1818 | 0.0224 | |
| | | 0.0395 | 9.95 | 2020 | 0.0217 | |
| | | 0.0395 | 10.95 | 2222 | 0.0191 | |
| | | 0.0395 | 11.94 | 2424 | 0.0156 | |
| | | 0.0303 | 12.94 | 2626 | 0.0164 | |
| | | 0.0303 | 13.93 | 2828 | 0.0146 | |
| | | 0.0226 | 14.93 | 3030 | 0.0124 | |
| | | 0.0226 | 15.92 | 3232 | 0.0127 | |
| | | 0.0226 | 16.92 | 3434 | 0.0115 | |
| | | 0.0176 | 17.91 | 3636 | 0.0123 | |
| | | 0.0176 | 18.91 | 3838 | 0.0115 | |
| | | 0.0146 | 19.9 | 4040 | 0.0115 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.1 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.17.1 |
| | - Tokenizers 0.15.2 |
| |
|
