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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-10-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-10-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: 0.2965
- Accuracy: 0.8886
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3829 | 1.0 | 2124 | 0.6337 | 0.8424 |
| 1.0008 | 2.0 | 4248 | 0.4279 | 0.8789 |
| 0.8108 | 3.0 | 6372 | 0.3942 | 0.8808 |
| 0.7122 | 4.0 | 8496 | 0.3775 | 0.8769 |
| 0.6473 | 5.0 | 10620 | 0.3395 | 0.8816 |
| 0.622 | 6.0 | 12744 | 0.3346 | 0.8806 |
| 0.5915 | 7.0 | 14868 | 0.3135 | 0.8842 |
| 0.5661 | 8.0 | 16992 | 0.3008 | 0.8887 |
| 0.559 | 9.0 | 19116 | 0.2914 | 0.8910 |
| 0.5623 | 10.0 | 21240 | 0.2965 | 0.8886 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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