---
library_name: transformers
license: apache-2.0
base_model: AlexeySorokin/ossbert-onc-unlab-from_multilingual-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-from_multilingual-bs64-5epochs](https://huggingface.co/AlexeySorokin/ossbert-onc-unlab-from_multilingual-bs64-5epochs) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2180
- Accuracy: 95.3662
- Sentence accuracy: 61.1009

## 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Sentence accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| No log        | 0.3663 | 200  | 0.7365          | 85.6227  | 26.4220           |
| No log        | 0.7326 | 400  | 0.4917          | 89.7247  | 35.4128           |
| 1.0818        | 1.0989 | 600  | 0.3859          | 91.3683  | 42.0183           |
| 1.0818        | 1.4652 | 800  | 0.3291          | 92.7312  | 48.0734           |
| 0.3537        | 1.8315 | 1000 | 0.3010          | 93.3191  | 50.4587           |
| 0.3537        | 2.1978 | 1200 | 0.2756          | 93.9738  | 52.6606           |
| 0.3537        | 2.5641 | 1400 | 0.2665          | 94.2678  | 54.6789           |
| 0.2244        | 2.9304 | 1600 | 0.2540          | 94.4949  | 56.5138           |
| 0.2244        | 3.2967 | 1800 | 0.2494          | 94.6686  | 55.0459           |
| 0.1549        | 3.6630 | 2000 | 0.2410          | 95.0695  | 60.1835           |
| 0.1549        | 4.0293 | 2200 | 0.2380          | 95.0027  | 59.6330           |
| 0.1549        | 4.3956 | 2400 | 0.2393          | 94.9759  | 58.3486           |
| 0.1165        | 4.7619 | 2600 | 0.2350          | 95.1897  | 59.8165           |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2