File size: 2,572 Bytes
eae0215 6aff6f5 eae0215 f62d69e eae0215 6aff6f5 eae0215 f62d69e eae0215 f62d69e eae0215 f62d69e eae0215 f62d69e eae0215 |
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 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- pritamdeka/cord-19-abstract
model-index:
- name: PubMedBert-abstract-cord19
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. -->
# pubmedbert-abstract-cord19
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the [pritamdeka/cord-19-abstract](https://huggingface.co/datasets/pritamdeka/cord-19-abstract) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3005
## 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
- lr_scheduler_warmup_steps: 10000
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.3774 | 0.15 | 5000 | 1.3212 |
| 1.3937 | 0.29 | 10000 | 1.4059 |
| 1.6812 | 0.44 | 15000 | 1.6174 |
| 1.4712 | 0.59 | 20000 | 1.4383 |
| 1.4293 | 0.73 | 25000 | 1.4356 |
| 1.4155 | 0.88 | 30000 | 1.4283 |
| 1.3963 | 1.03 | 35000 | 1.4135 |
| 1.3718 | 1.18 | 40000 | 1.3948 |
| 1.369 | 1.32 | 45000 | 1.3961 |
| 1.354 | 1.47 | 50000 | 1.3788 |
| 1.3399 | 1.62 | 55000 | 1.3866 |
| 1.3289 | 1.76 | 60000 | 1.3630 |
| 1.3155 | 1.91 | 65000 | 1.3609 |
| 1.2976 | 2.06 | 70000 | 1.3489 |
| 1.2783 | 2.2 | 75000 | 1.3333 |
| 1.2696 | 2.35 | 80000 | 1.3260 |
| 1.2607 | 2.5 | 85000 | 1.3232 |
| 1.2547 | 2.64 | 90000 | 1.3034 |
| 1.2495 | 2.79 | 95000 | 1.3035 |
| 1.2404 | 2.94 | 100000 | 1.3029 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
|