---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: WMAC
  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. -->

# WMAC

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3746
- Wer: 60.4747

## 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: 2.5e-05
- train_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 700
- training_steps: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4011        | 0.4755 | 1000 | 0.4190          | 70.8256 |
| 0.2792        | 0.9510 | 2000 | 0.2993          | 60.8256 |
| 0.1901        | 1.4265 | 3000 | 0.2710          | 61.0217 |
| 0.1361        | 1.9020 | 4000 | 0.2524          | 59.0402 |
| 0.0730        | 2.3776 | 5000 | 0.2787          | 60.8772 |
| 0.0592        | 2.8531 | 6000 | 0.2807          | 60.0826 |
| 0.0213        | 3.3286 | 7000 | 0.3746          | 60.4747 |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2