---
library_name: transformers
license: apache-2.0
base_model: mouseyy/result_data-1
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: result_data_2-3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: uk
      split: test
      args: uk
    metrics:
    - name: Wer
      type: wer
      value: 0.3390885932635154
---

<!-- 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. -->

# result_data_2-3

This model is a fine-tuned version of [mouseyy/result_data-1](https://huggingface.co/mouseyy/result_data-1) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2363
- Wer: 0.3391
- Cer: 0.1637

## 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: 4.1584533148786865e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch 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: 135
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 0.1644        | 0.9099 | 1000 | 0.2423          | 0.3691 | 0.1712 |
| 0.1373        | 1.8198 | 2000 | 0.2359          | 0.3586 | 0.1699 |
| 0.1219        | 2.7298 | 3000 | 0.2351          | 0.3487 | 0.1665 |
| 0.1106        | 3.6397 | 4000 | 0.2399          | 0.3447 | 0.1667 |
| 0.0986        | 4.5496 | 5000 | 0.2418          | 0.3388 | 0.1639 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0