---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: defect-classification-scibert-baseline-20-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-20-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: 0.2422
- Accuracy: 0.9124

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3805        | 1.0   | 2124  | 0.7077          | 0.8454   |
| 0.9347        | 2.0   | 4248  | 0.4424          | 0.8740   |
| 0.782         | 3.0   | 6372  | 0.3730          | 0.8907   |
| 0.6677        | 4.0   | 8496  | 0.3447          | 0.8957   |
| 0.6018        | 5.0   | 10620 | 0.3021          | 0.9057   |
| 0.5746        | 6.0   | 12744 | 0.3155          | 0.8961   |
| 0.5257        | 7.0   | 14868 | 0.2747          | 0.9100   |
| 0.5162        | 8.0   | 16992 | 0.2639          | 0.9104   |
| 0.4955        | 9.0   | 19116 | 0.2921          | 0.8975   |
| 0.4763        | 10.0  | 21240 | 0.2684          | 0.9036   |
| 0.4579        | 11.0  | 23364 | 0.2657          | 0.9069   |
| 0.454         | 12.0  | 25488 | 0.2535          | 0.9114   |
| 0.4384        | 13.0  | 27612 | 0.2626          | 0.9039   |
| 0.428         | 14.0  | 29736 | 0.2620          | 0.9011   |
| 0.4262        | 15.0  | 31860 | 0.2411          | 0.9141   |
| 0.425         | 16.0  | 33984 | 0.2586          | 0.9035   |
| 0.4141        | 17.0  | 36108 | 0.2446          | 0.9117   |
| 0.4129        | 18.0  | 38232 | 0.2506          | 0.9073   |
| 0.4105        | 19.0  | 40356 | 0.2424          | 0.9132   |
| 0.4099        | 20.0  | 42480 | 0.2422          | 0.9124   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0