---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-1b-Yspeed
  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. -->

# wav2vec2-1b-Yspeed

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9193
- Cer: 22.7561

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 50
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 14.1833       | 0.2580 | 200  | 4.5491          | 97.4389 |
| 2.5916        | 0.5160 | 400  | 2.0400          | 48.7077 |
| 1.351         | 0.7741 | 600  | 1.9023          | 46.5695 |
| 1.0665        | 1.0321 | 800  | 1.2533          | 34.7039 |
| 0.8141        | 1.2901 | 1000 | 1.3127          | 32.2016 |
| 0.7672        | 1.5481 | 1200 | 1.3379          | 33.9814 |
| 0.6847        | 1.8062 | 1400 | 1.2278          | 32.0489 |
| 0.5985        | 2.0642 | 1600 | 1.1310          | 28.4657 |
| 0.5208        | 2.3222 | 1800 | 1.2212          | 29.4995 |
| 0.4664        | 2.5802 | 2000 | 1.0708          | 26.2512 |
| 0.4379        | 2.8383 | 2200 | 1.0705          | 26.3804 |
| 0.4332        | 3.0963 | 2400 | 1.0949          | 27.4260 |
| 0.3778        | 3.3543 | 2600 | 0.9809          | 25.3936 |
| 0.3273        | 3.6123 | 2800 | 1.0045          | 24.5418 |
| 0.3117        | 3.8703 | 3000 | 0.9171          | 23.0146 |
| 0.2586        | 4.1284 | 3200 | 0.9051          | 22.5329 |
| 0.2273        | 4.3864 | 3400 | 0.8966          | 22.3508 |
| 0.2169        | 4.6444 | 3600 | 0.9430          | 23.2202 |
| 0.2159        | 4.9024 | 3800 | 0.9193          | 22.7561 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.3.1.post100
- Datasets 2.19.1
- Tokenizers 0.20.1