---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E30_sp
  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-E30_sp

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4665
- Cer: 30.6287

## 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: 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 32.3037       | 0.1289 | 200  | 5.0215          | 100.0   |
| 4.9642        | 0.2579 | 400  | 4.6861          | 100.0   |
| 4.8422        | 0.3868 | 600  | 4.7308          | 100.0   |
| 4.7474        | 0.5158 | 800  | 4.6660          | 97.7203 |
| 4.6975        | 0.6447 | 1000 | 4.5628          | 97.9436 |
| 4.6688        | 0.7737 | 1200 | 4.5418          | 97.7262 |
| 4.6225        | 0.9026 | 1400 | 4.5220          | 97.9377 |
| 4.5627        | 1.0316 | 1600 | 4.5568          | 97.2092 |
| 4.5233        | 1.1605 | 1800 | 4.4908          | 96.2926 |
| 4.4088        | 1.2895 | 2000 | 4.4416          | 95.4465 |
| 4.0188        | 1.4184 | 2200 | 3.7750          | 77.5206 |
| 3.2832        | 1.5474 | 2400 | 3.1100          | 61.0576 |
| 2.7716        | 1.6763 | 2600 | 2.6530          | 51.1222 |
| 2.4346        | 1.8053 | 2800 | 2.3400          | 46.3220 |
| 2.1907        | 1.9342 | 3000 | 2.0907          | 40.3290 |
| 2.0173        | 2.0632 | 3200 | 1.9195          | 39.0541 |
| 1.8574        | 2.1921 | 3400 | 1.8219          | 37.3796 |
| 1.6992        | 2.3211 | 3600 | 1.7006          | 34.4947 |
| 1.623         | 2.4500 | 3800 | 1.6380          | 34.0129 |
| 1.5586        | 2.5790 | 4000 | 1.5646          | 32.3913 |
| 1.5001        | 2.7079 | 4200 | 1.4950          | 31.5570 |
| 1.4357        | 2.8369 | 4400 | 1.4842          | 31.3337 |
| 1.3935        | 2.9658 | 4600 | 1.4665          | 30.6287 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0