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---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: defect-classification-scibert-baseline-25-epochs
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. -->
# defect-classification-scibert-baseline-25-epochs
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: 0.2317
- Accuracy: 0.9075
## 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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3655 | 1.0 | 2124 | 1.1784 | 0.8208 |
| 0.9439 | 2.0 | 4248 | 0.6611 | 0.8474 |
| 0.7364 | 3.0 | 6372 | 0.5215 | 0.8561 |
| 0.6355 | 4.0 | 8496 | 0.4250 | 0.8669 |
| 0.5592 | 5.0 | 10620 | 0.3694 | 0.8740 |
| 0.5411 | 6.0 | 12744 | 0.3482 | 0.8754 |
| 0.5056 | 7.0 | 14868 | 0.3418 | 0.8757 |
| 0.4838 | 8.0 | 16992 | 0.2492 | 0.9132 |
| 0.469 | 9.0 | 19116 | 0.3220 | 0.8785 |
| 0.4468 | 10.0 | 21240 | 0.2693 | 0.8964 |
| 0.432 | 11.0 | 23364 | 0.2756 | 0.8913 |
| 0.4256 | 12.0 | 25488 | 0.2545 | 0.9019 |
| 0.4158 | 13.0 | 27612 | 0.2431 | 0.9061 |
| 0.3961 | 14.0 | 29736 | 0.2532 | 0.9001 |
| 0.3972 | 15.0 | 31860 | 0.2441 | 0.9025 |
| 0.3931 | 16.0 | 33984 | 0.2456 | 0.9008 |
| 0.3882 | 17.0 | 36108 | 0.2536 | 0.8971 |
| 0.3846 | 18.0 | 38232 | 0.2421 | 0.9029 |
| 0.3806 | 19.0 | 40356 | 0.2547 | 0.8960 |
| 0.3761 | 20.0 | 42480 | 0.2527 | 0.8956 |
| 0.3648 | 21.0 | 44604 | 0.2475 | 0.8979 |
| 0.3684 | 22.0 | 46728 | 0.2333 | 0.9079 |
| 0.3679 | 23.0 | 48852 | 0.2300 | 0.9095 |
| 0.3683 | 24.0 | 50976 | 0.2347 | 0.9060 |
| 0.3632 | 25.0 | 53100 | 0.2317 | 0.9075 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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