---
library_name: transformers
base_model: AlexeySorokin/ossbert-onc-unlab-bs64-5epochs
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer_output
  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. -->

# trainer_output

This model is a fine-tuned version of [AlexeySorokin/ossbert-onc-unlab-bs64-5epochs](https://huggingface.co/AlexeySorokin/ossbert-onc-unlab-bs64-5epochs) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4048
- Accuracy: 95.0828
- Sentence accuracy: 57.6147

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy | Sentence accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:-----------------:|
| 1.1201        | 0.9158  | 500   | 0.4242          | 91.5286  | 40.9174           |
| 0.3523        | 1.8315  | 1000  | 0.3102          | 92.9717  | 48.6239           |
| 0.2212        | 2.7473  | 1500  | 0.2753          | 93.8402  | 52.6606           |
| 0.1566        | 3.6630  | 2000  | 0.2708          | 93.9872  | 52.1101           |
| 0.1149        | 4.5788  | 2500  | 0.2717          | 94.4148  | 52.4771           |
| 0.0859        | 5.4945  | 3000  | 0.2636          | 95.0561  | 57.7982           |
| 0.0632        | 6.4103  | 3500  | 0.2898          | 94.8691  | 56.8807           |
| 0.0471        | 7.3260  | 4000  | 0.2927          | 94.9759  | 57.2477           |
| 0.0351        | 8.2418  | 4500  | 0.3040          | 94.8824  | 57.2477           |
| 0.0267        | 9.1575  | 5000  | 0.3026          | 95.0160  | 57.9817           |
| 0.0206        | 10.0733 | 5500  | 0.3088          | 95.2165  | 58.8991           |
| 0.0158        | 10.9890 | 6000  | 0.3278          | 94.8824  | 57.7982           |
| 0.0118        | 11.9048 | 6500  | 0.3241          | 95.1229  | 58.7156           |
| 0.0095        | 12.8205 | 7000  | 0.3374          | 95.2699  | 58.3486           |
| 0.0088        | 13.7363 | 7500  | 0.3647          | 94.8557  | 56.5138           |
| 0.0076        | 14.6520 | 8000  | 0.3639          | 94.9225  | 57.0642           |
| 0.0077        | 15.5678 | 8500  | 0.3574          | 95.2432  | 58.8991           |
| 0.006         | 16.4835 | 9000  | 0.3778          | 95.1630  | 57.6147           |
| 0.0045        | 17.3993 | 9500  | 0.3738          | 95.3634  | 59.0826           |
| 0.0049        | 18.3150 | 10000 | 0.3824          | 95.1897  | 57.4312           |
| 0.0029        | 19.2308 | 10500 | 0.3893          | 94.9626  | 57.7982           |
| 0.0033        | 20.1465 | 11000 | 0.4039          | 95.1096  | 58.1651           |
| 0.0038        | 21.0623 | 11500 | 0.4056          | 95.1096  | 58.7156           |
| 0.0032        | 21.9780 | 12000 | 0.4048          | 95.0828  | 57.6147           |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2