---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E50_pause
  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-E50_pause

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: 1.0142
- Cer: 29.0179

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 29.2433       | 0.1289 | 200  | 4.9344          | 100.0   |
| 4.8669        | 0.2579 | 400  | 4.6589          | 100.0   |
| 4.7421        | 0.3868 | 600  | 4.6241          | 98.4258 |
| 4.6589        | 0.5158 | 800  | 4.5763          | 97.6269 |
| 4.5978        | 0.6447 | 1000 | 4.6357          | 97.5446 |
| 4.5014        | 0.7737 | 1200 | 4.3404          | 95.6884 |
| 3.8915        | 0.9026 | 1400 | 3.3848          | 65.5193 |
| 2.9112        | 1.0316 | 1600 | 2.6761          | 58.4763 |
| 2.4372        | 1.1605 | 1800 | 2.3130          | 48.8369 |
| 2.1033        | 1.2895 | 2000 | 2.0994          | 47.3391 |
| 1.8883        | 1.4184 | 2200 | 1.7943          | 42.6574 |
| 1.7159        | 1.5474 | 2400 | 1.7197          | 41.7998 |
| 1.5891        | 1.6763 | 2600 | 1.5193          | 38.6631 |
| 1.443         | 1.8053 | 2800 | 1.4734          | 37.8994 |
| 1.3674        | 1.9342 | 3000 | 1.3481          | 34.1988 |
| 1.2286        | 2.0632 | 3200 | 1.2702          | 32.8301 |
| 1.1511        | 2.1921 | 3400 | 1.2076          | 33.0592 |
| 1.0793        | 2.3211 | 3600 | 1.1945          | 33.2178 |
| 1.0503        | 2.4500 | 3800 | 1.1009          | 30.6039 |
| 1.016         | 2.5790 | 4000 | 1.0903          | 30.3102 |
| 0.988         | 2.7079 | 4200 | 1.0930          | 31.2441 |
| 0.957         | 2.8369 | 4400 | 1.0501          | 30.1692 |
| 0.9308        | 2.9658 | 4600 | 1.0142          | 29.0179 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1