File size: 2,678 Bytes
941d272 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
model-index:
- name: scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs
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. -->
# scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs
This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0407
## 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: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.1073 | 1.0 | 3301 | 0.0633 |
| 0.0657 | 2.0 | 6602 | 0.0563 |
| 0.059 | 3.0 | 9903 | 0.0536 |
| 0.0556 | 4.0 | 13204 | 0.0518 |
| 0.0531 | 5.0 | 16505 | 0.0496 |
| 0.0511 | 6.0 | 19806 | 0.0489 |
| 0.0498 | 7.0 | 23107 | 0.0477 |
| 0.0488 | 8.0 | 26408 | 0.0468 |
| 0.0478 | 9.0 | 29709 | 0.0464 |
| 0.0467 | 10.0 | 33010 | 0.0455 |
| 0.0467 | 11.0 | 36311 | 0.0450 |
| 0.0458 | 12.0 | 39612 | 0.0454 |
| 0.0449 | 13.0 | 42913 | 0.0441 |
| 0.0447 | 14.0 | 46214 | 0.0432 |
| 0.044 | 15.0 | 49515 | 0.0428 |
| 0.0436 | 16.0 | 52816 | 0.0429 |
| 0.0433 | 17.0 | 56117 | 0.0428 |
| 0.0431 | 18.0 | 59418 | 0.0423 |
| 0.0427 | 19.0 | 62719 | 0.0419 |
| 0.0425 | 20.0 | 66020 | 0.0420 |
| 0.0422 | 21.0 | 69321 | 0.0412 |
| 0.0422 | 22.0 | 72622 | 0.0413 |
| 0.0416 | 23.0 | 75923 | 0.0407 |
| 0.0415 | 24.0 | 79224 | 0.0410 |
| 0.0411 | 25.0 | 82525 | 0.0408 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2
|