---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-1b-E30_freq
  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-E30_freq

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: 0.4977
- Cer: 13.7277

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 13.4278       | 0.2580 | 200  | 4.0083          | 87.1123 |
| 2.1559        | 0.5160 | 400  | 1.8970          | 40.9833 |
| 1.3277        | 0.7741 | 600  | 1.2101          | 31.0620 |
| 1.162         | 1.0321 | 800  | 1.0824          | 26.5096 |
| 0.9949        | 1.2901 | 1000 | 0.9657          | 24.2246 |
| 0.9109        | 1.5481 | 1200 | 1.0152          | 24.8414 |
| 0.8943        | 1.8062 | 1400 | 0.8544          | 21.7869 |
| 0.7895        | 2.0642 | 1600 | 0.9202          | 22.9617 |
| 0.6679        | 2.3222 | 1800 | 0.9574          | 24.1835 |
| 0.6296        | 2.5802 | 2000 | 0.7541          | 19.2199 |
| 0.6245        | 2.8383 | 2200 | 0.7259          | 19.2728 |
| 0.5656        | 3.0963 | 2400 | 0.6447          | 17.3344 |
| 0.4821        | 3.3543 | 2600 | 0.6489          | 16.9878 |
| 0.4513        | 3.6123 | 2800 | 0.6556          | 17.5282 |
| 0.4285        | 3.8703 | 3000 | 0.6180          | 16.7234 |
| 0.374         | 4.1284 | 3200 | 0.5651          | 15.2314 |
| 0.3375        | 4.3864 | 3400 | 0.5135          | 13.8275 |
| 0.3158        | 4.6444 | 3600 | 0.4945          | 13.7688 |
| 0.2897        | 4.9024 | 3800 | 0.4977          | 13.7277 |


### Framework versions

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