---
library_name: transformers
base_model: nreimers/BERT-Tiny_L-2_H-128_A-2
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_trained
  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. -->

# bert_tiny_trained

This model is a fine-tuned version of [nreimers/BERT-Tiny_L-2_H-128_A-2](https://huggingface.co/nreimers/BERT-Tiny_L-2_H-128_A-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5820

## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 11   | 1.3285          |
| No log        | 2.0   | 22   | 1.3144          |
| No log        | 3.0   | 33   | 1.2977          |
| No log        | 4.0   | 44   | 1.2683          |
| No log        | 5.0   | 55   | 1.2476          |
| No log        | 6.0   | 66   | 1.2256          |
| No log        | 7.0   | 77   | 1.1961          |
| No log        | 8.0   | 88   | 1.1853          |
| No log        | 9.0   | 99   | 1.1625          |
| No log        | 10.0  | 110  | 1.1284          |
| No log        | 11.0  | 121  | 1.1036          |
| No log        | 12.0  | 132  | 1.0812          |
| No log        | 13.0  | 143  | 1.0573          |
| No log        | 14.0  | 154  | 1.0323          |
| No log        | 15.0  | 165  | 1.0092          |
| No log        | 16.0  | 176  | 0.9913          |
| No log        | 17.0  | 187  | 0.9725          |
| No log        | 18.0  | 198  | 0.9492          |
| No log        | 19.0  | 209  | 0.9269          |
| No log        | 20.0  | 220  | 0.9061          |
| No log        | 21.0  | 231  | 0.8869          |
| No log        | 22.0  | 242  | 0.8719          |
| No log        | 23.0  | 253  | 0.8521          |
| No log        | 24.0  | 264  | 0.8357          |
| No log        | 25.0  | 275  | 0.8169          |
| No log        | 26.0  | 286  | 0.8026          |
| No log        | 27.0  | 297  | 0.7936          |
| No log        | 28.0  | 308  | 0.7783          |
| No log        | 29.0  | 319  | 0.7677          |
| No log        | 30.0  | 330  | 0.7577          |
| No log        | 31.0  | 341  | 0.7516          |
| No log        | 32.0  | 352  | 0.7431          |
| No log        | 33.0  | 363  | 0.7355          |
| No log        | 34.0  | 374  | 0.7287          |
| No log        | 35.0  | 385  | 0.7220          |
| No log        | 36.0  | 396  | 0.7154          |
| No log        | 37.0  | 407  | 0.7119          |
| No log        | 38.0  | 418  | 0.7073          |
| No log        | 39.0  | 429  | 0.7025          |
| No log        | 40.0  | 440  | 0.6976          |
| No log        | 41.0  | 451  | 0.6931          |
| No log        | 42.0  | 462  | 0.6890          |
| No log        | 43.0  | 473  | 0.6859          |
| No log        | 44.0  | 484  | 0.6830          |
| No log        | 45.0  | 495  | 0.6807          |
| 0.7544        | 46.0  | 506  | 0.6785          |
| 0.7544        | 47.0  | 517  | 0.6774          |
| 0.7544        | 48.0  | 528  | 0.6769          |
| 0.7544        | 49.0  | 539  | 0.6768          |
| 0.7544        | 50.0  | 550  | 0.6767          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0