---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E30_speed3
  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_speed3

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: 1.2614
- Cer: 27.0035

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 44.2054       | 0.1289 | 200  | 5.4975          | 100.0   |
| 5.0916        | 0.2579 | 400  | 4.7077          | 100.0   |
| 4.8758        | 0.3868 | 600  | 4.6568          | 100.0   |
| 4.8539        | 0.5158 | 800  | 4.6120          | 100.0   |
| 4.7493        | 0.6447 | 1000 | 4.5950          | 100.0   |
| 4.5763        | 0.7737 | 1200 | 4.3522          | 98.5076 |
| 3.7522        | 0.9026 | 1400 | 3.0023          | 54.3478 |
| 2.71          | 1.0316 | 1600 | 2.6582          | 48.0200 |
| 2.3514        | 1.1605 | 1800 | 2.3269          | 42.1034 |
| 1.9845        | 1.2895 | 2000 | 1.9847          | 36.9918 |
| 1.7755        | 1.4184 | 2200 | 1.8688          | 35.3643 |
| 1.6234        | 1.5474 | 2400 | 1.7565          | 33.8837 |
| 1.5417        | 1.6763 | 2600 | 1.7060          | 33.1199 |
| 1.4338        | 1.8053 | 2800 | 1.6633          | 33.5194 |
| 1.3403        | 1.9342 | 3000 | 1.5921          | 32.7791 |
| 1.2466        | 2.0632 | 3200 | 1.5050          | 31.0458 |
| 1.1278        | 2.1921 | 3400 | 1.4261          | 29.5828 |
| 1.0863        | 2.3211 | 3600 | 1.3675          | 28.9189 |
| 1.0236        | 2.4500 | 3800 | 1.3119          | 27.9318 |
| 0.9973        | 2.5790 | 4000 | 1.2762          | 27.2150 |
| 0.9749        | 2.7079 | 4200 | 1.3005          | 27.4677 |
| 0.9365        | 2.8369 | 4400 | 1.2889          | 27.6204 |
| 0.8997        | 2.9658 | 4600 | 1.2614          | 27.0035 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3