---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results
  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. -->

# results

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1958
- Accuracy: 0.9431
- F1: 0.9434

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.2569        | 0.1280 | 50   | 0.2415          | 0.9041   | 0.8996 |
| 0.2055        | 0.2559 | 100  | 0.2228          | 0.9157   | 0.9194 |
| 0.2424        | 0.3839 | 150  | 0.1831          | 0.9311   | 0.9310 |
| 0.2092        | 0.5118 | 200  | 0.1808          | 0.9313   | 0.9316 |
| 0.1878        | 0.6398 | 250  | 0.1993          | 0.9244   | 0.9273 |
| 0.2077        | 0.7678 | 300  | 0.1705          | 0.9357   | 0.9367 |
| 0.1937        | 0.8957 | 350  | 0.1847          | 0.9282   | 0.9310 |
| 0.1448        | 1.0230 | 400  | 0.1701          | 0.9366   | 0.9361 |
| 0.1034        | 1.1510 | 450  | 0.1763          | 0.9403   | 0.9403 |
| 0.1395        | 1.2790 | 500  | 0.1854          | 0.9396   | 0.9401 |
| 0.1141        | 1.4069 | 550  | 0.1774          | 0.9389   | 0.9381 |
| 0.1323        | 1.5349 | 600  | 0.1716          | 0.9389   | 0.9377 |
| 0.1824        | 1.6628 | 650  | 0.1866          | 0.9381   | 0.9398 |
| 0.133         | 1.7908 | 700  | 0.1716          | 0.9415   | 0.9414 |
| 0.1054        | 1.9187 | 750  | 0.1651          | 0.944    | 0.9442 |
| 0.0473        | 2.0461 | 800  | 0.1755          | 0.944    | 0.9440 |
| 0.0458        | 2.1740 | 850  | 0.1917          | 0.9426   | 0.9427 |
| 0.1082        | 2.3020 | 900  | 0.2014          | 0.9418   | 0.9424 |
| 0.0621        | 2.4299 | 950  | 0.2019          | 0.9416   | 0.9418 |
| 0.0773        | 2.5579 | 1000 | 0.1988          | 0.9412   | 0.9411 |
| 0.1104        | 2.6859 | 1050 | 0.2031          | 0.9418   | 0.9413 |
| 0.079         | 2.8138 | 1100 | 0.1962          | 0.9431   | 0.9432 |
| 0.0717        | 2.9418 | 1150 | 0.1958          | 0.9431   | 0.9434 |


### Framework versions

- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2