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

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: 3.6299
- Cer: 69.5709

## 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 56.9189       | 0.13  | 200  | 17.3335         | 100.0   |
| 24.9477       | 0.26  | 400  | 5.2898          | 93.4002 |
| 22.4883       | 0.39  | 600  | 5.1855          | 91.7503 |
| 23.6577       | 0.52  | 800  | 5.5828          | 93.8097 |
| 12.0508       | 0.64  | 1000 | 5.5876          | 92.9788 |
| 6.9102        | 0.77  | 1200 | 5.2180          | 93.1153 |
| 5.2937        | 0.9   | 1400 | 4.6411          | 93.6613 |
| 4.6224        | 1.03  | 1600 | 4.7614          | 93.7088 |
| 4.6148        | 1.16  | 1800 | 4.8569          | 93.0916 |
| 4.6129        | 1.29  | 2000 | 4.6641          | 92.5693 |
| 4.5837        | 1.42  | 2200 | 4.7341          | 93.5664 |
| 4.5465        | 1.55  | 2400 | 4.7580          | 93.3646 |
| 4.5042        | 1.68  | 2600 | 4.8342          | 93.4180 |
| 4.4535        | 1.81  | 2800 | 4.8323          | 93.4952 |
| 4.3942        | 1.93  | 3000 | 4.7891          | 92.1538 |
| 4.347         | 2.06  | 3200 | 4.5461          | 92.4150 |
| 4.3064        | 2.19  | 3400 | 4.7049          | 92.0114 |
| 4.301         | 2.32  | 3600 | 4.6162          | 92.3438 |
| 4.2107        | 2.45  | 3800 | 4.5264          | 92.3497 |
| 4.1768        | 2.58  | 4000 | 4.4067          | 87.1090 |
| 4.1395        | 2.71  | 4200 | 4.5684          | 90.6048 |
| 4.0568        | 2.84  | 4400 | 4.4142          | 87.7856 |
| 4.0007        | 2.97  | 4600 | 4.2861          | 87.7619 |
| 3.9426        | 3.09  | 4800 | 4.2750          | 87.4236 |
| 3.8207        | 3.22  | 5000 | 4.2217          | 84.2424 |
| 3.7678        | 3.35  | 5200 | 4.1129          | 81.1324 |
| 3.7522        | 3.48  | 5400 | 4.0891          | 83.2512 |
| 3.6666        | 3.61  | 5600 | 4.0328          | 80.0107 |
| 3.587         | 3.74  | 5800 | 4.0241          | 80.2837 |
| 3.5184        | 3.87  | 6000 | 4.0116          | 81.8209 |
| 3.449         | 4.0   | 6200 | 3.9031          | 76.4437 |
| 3.3503        | 4.13  | 6400 | 3.8643          | 75.8680 |
| 3.2541        | 4.26  | 6600 | 3.8508          | 72.4850 |
| 3.1987        | 4.38  | 6800 | 3.8425          | 71.8203 |
| 3.1435        | 4.51  | 7000 | 3.7289          | 71.6719 |
| 3.0583        | 4.64  | 7200 | 3.6855          | 70.1703 |
| 3.0443        | 4.77  | 7400 | 3.6365          | 69.6540 |
| 3.0508        | 4.9   | 7600 | 3.6299          | 69.5709 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0