---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-aiish-clp
  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. -->

# xlsr-aiish-clp

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.3154

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.176         | 2.4845  | 200  | 2.7099          | 1.0    |
| 2.5595        | 4.9689  | 400  | 1.7974          | 1.0    |
| 1.1648        | 7.4534  | 600  | 0.1544          | 0.6039 |
| 0.3992        | 9.9379  | 800  | 0.0722          | 0.5465 |
| 0.2507        | 12.4224 | 1000 | 0.0451          | 0.4670 |
| 0.176         | 14.9068 | 1200 | 0.0316          | 0.3729 |
| 0.1324        | 17.3913 | 1400 | 0.0155          | 0.3655 |
| 0.1193        | 19.8758 | 1600 | 0.0075          | 0.3313 |
| 0.0897        | 22.3602 | 1800 | 0.0201          | 0.3313 |
| 0.0825        | 24.8447 | 2000 | 0.0035          | 0.3117 |
| 0.054         | 27.3292 | 2200 | 0.0058          | 0.3154 |
| 0.0579        | 29.8137 | 2400 | 0.0013          | 0.3081 |
| 0.0529        | 32.2981 | 2600 | 0.0028          | 0.3093 |
| 0.0418        | 34.7826 | 2800 | 0.0043          | 0.3081 |
| 0.0402        | 37.2671 | 3000 | 0.0084          | 0.3117 |
| 0.0366        | 39.7516 | 3200 | 0.0006          | 0.3093 |
| 0.0326        | 42.2360 | 3400 | 0.0031          | 0.3117 |
| 0.0266        | 44.7205 | 3600 | 0.0029          | 0.3166 |
| 0.0268        | 47.2050 | 3800 | 0.0009          | 0.3081 |
| 0.024         | 49.6894 | 4000 | 0.0014          | 0.3093 |
| 0.0185        | 52.1739 | 4200 | 0.0001          | 0.3081 |
| 0.0277        | 54.6584 | 4400 | 0.0011          | 0.3068 |
| 0.0179        | 57.1429 | 4600 | 0.0026          | 0.3093 |
| 0.0161        | 59.6273 | 4800 | 0.0086          | 0.3142 |
| 0.0177        | 62.1118 | 5000 | 0.0004          | 0.3130 |
| 0.0184        | 64.5963 | 5200 | 0.0009          | 0.3130 |
| 0.0131        | 67.0807 | 5400 | 0.0022          | 0.3166 |
| 0.017         | 69.5652 | 5600 | 0.0026          | 0.3105 |
| 0.0083        | 72.0497 | 5800 | 0.0023          | 0.3081 |
| 0.0082        | 74.5342 | 6000 | 0.0001          | 0.3093 |
| 0.0068        | 77.0186 | 6200 | 0.0001          | 0.3142 |
| 0.0072        | 79.5031 | 6400 | 0.0002          | 0.3142 |
| 0.0097        | 81.9876 | 6600 | 0.0001          | 0.3142 |
| 0.0087        | 84.4720 | 6800 | 0.0001          | 0.3154 |
| 0.0065        | 86.9565 | 7000 | 0.0000          | 0.3154 |
| 0.0072        | 89.4410 | 7200 | 0.0000          | 0.3154 |
| 0.0065        | 91.9255 | 7400 | 0.0001          | 0.3154 |
| 0.0044        | 94.4099 | 7600 | 0.0001          | 0.3154 |
| 0.0053        | 96.8944 | 7800 | 0.0000          | 0.3154 |
| 0.005         | 99.3789 | 8000 | 0.0000          | 0.3154 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1