---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: testlaibasettsgopdata
  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. -->

# testlaibasettsgopdata

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0930
- Wer: 0.1682

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.2716        | 1.05  | 500   | 3.0550          | 1.0    |
| 1.8262        | 2.11  | 1000  | 0.2669          | 0.3023 |
| 0.5469        | 3.16  | 1500  | 0.1809          | 0.2281 |
| 0.3541        | 4.21  | 2000  | 0.1541          | 0.2185 |
| 0.3367        | 5.26  | 2500  | 0.1432          | 0.2054 |
| 0.2792        | 6.32  | 3000  | 0.1218          | 0.2023 |
| 0.2411        | 7.37  | 3500  | 0.1136          | 0.2029 |
| 0.2041        | 8.42  | 4000  | 0.1423          | 0.2025 |
| 0.2262        | 9.47  | 4500  | 0.1294          | 0.1968 |
| 0.1921        | 10.53 | 5000  | 0.1237          | 0.1952 |
| 0.1877        | 11.58 | 5500  | 0.1043          | 0.1890 |
| 0.176         | 12.63 | 6000  | 0.1272          | 0.1935 |
| 0.1236        | 13.68 | 6500  | 0.1352          | 0.1902 |
| 0.1473        | 14.74 | 7000  | 0.1257          | 0.1874 |
| 0.1748        | 15.79 | 7500  | 0.1190          | 0.1854 |
| 0.1147        | 16.84 | 8000  | 0.1213          | 0.1914 |
| 0.1508        | 17.89 | 8500  | 0.1262          | 0.1813 |
| 0.1061        | 18.95 | 9000  | 0.1148          | 0.1802 |
| 0.1182        | 20.0  | 9500  | 0.1034          | 0.1758 |
| 0.1144        | 21.05 | 10000 | 0.1123          | 0.1769 |
| 0.0885        | 22.11 | 10500 | 0.1043          | 0.1735 |
| 0.0797        | 23.16 | 11000 | 0.1004          | 0.1712 |
| 0.0729        | 24.21 | 11500 | 0.1045          | 0.1703 |
| 0.0718        | 25.26 | 12000 | 0.1064          | 0.1712 |
| 0.0668        | 26.32 | 12500 | 0.1050          | 0.1687 |
| 0.0599        | 27.37 | 13000 | 0.0965          | 0.1677 |
| 0.0702        | 28.42 | 13500 | 0.0930          | 0.1682 |
| 0.0942        | 29.47 | 14000 | 0.0959          | 0.1674 |


### Framework versions

- Transformers 4.17.0
- Pytorch 2.5.1+cu121
- Datasets 1.18.3
- Tokenizers 0.20.3