---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: muk-english-digits-classification
  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. -->

# muk-english-digits-classification

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8012
- Accuracy: 1.0

## 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: 8
- eval_batch_size: 1
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.3974        | 1.0   | 32   | 2.3805          | 0.1875   |
| 2.3542        | 2.0   | 64   | 2.3080          | 0.1875   |
| 2.2986        | 3.0   | 96   | 2.1997          | 0.3438   |
| 2.1947        | 4.0   | 128  | 2.0517          | 0.4062   |
| 2.0741        | 5.0   | 160  | 1.9182          | 0.4062   |
| 1.9479        | 6.0   | 192  | 1.8475          | 0.4688   |
| 1.8934        | 7.0   | 224  | 1.6724          | 0.5938   |
| 1.687         | 8.0   | 256  | 1.5422          | 0.6875   |
| 1.5745        | 9.0   | 288  | 1.3878          | 0.875    |
| 1.5288        | 10.0  | 320  | 1.2905          | 0.875    |
| 1.3518        | 11.0  | 352  | 1.1875          | 0.9375   |
| 1.2558        | 12.0  | 384  | 1.0936          | 0.9375   |
| 1.1538        | 13.0  | 416  | 1.0296          | 0.9688   |
| 1.186         | 14.0  | 448  | 0.9815          | 0.9688   |
| 1.033         | 15.0  | 480  | 0.9271          | 1.0      |
| 0.9828        | 16.0  | 512  | 0.8811          | 1.0      |
| 0.995         | 17.0  | 544  | 0.8454          | 0.9688   |
| 0.9213        | 18.0  | 576  | 0.8176          | 1.0      |
| 0.9313        | 19.0  | 608  | 0.8048          | 1.0      |
| 0.9029        | 20.0  | 640  | 0.8012          | 1.0      |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1