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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-cv_vi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: vi
split: test
args: vi
metrics:
- name: Wer
type: wer
value: 0.663156740155753
---
<!-- 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-cv_vi
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3858
- Wer: 0.6632
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 14.1667 | 9.2 | 200 | 4.5633 | 1.0 |
| 3.6334 | 18.39 | 400 | 3.4332 | 1.0 |
| 1.938 | 27.59 | 600 | 1.2434 | 0.7082 |
| 0.3082 | 36.78 | 800 | 1.2288 | 0.6534 |
| 0.1766 | 45.98 | 1000 | 1.2915 | 0.6500 |
| 0.1287 | 55.17 | 1200 | 1.3452 | 0.6269 |
| 0.1043 | 64.37 | 1400 | 1.4746 | 0.6395 |
| 0.0834 | 73.56 | 1600 | 1.4731 | 0.6347 |
| 0.0837 | 82.76 | 1800 | 1.5893 | 0.6493 |
| 0.0711 | 91.95 | 2000 | 1.6205 | 0.6522 |
| 0.0672 | 101.15 | 2200 | 1.5513 | 0.6503 |
| 0.0745 | 110.34 | 2400 | 1.6509 | 0.6774 |
| 0.07 | 119.54 | 2600 | 1.6779 | 0.6543 |
| 0.0492 | 128.74 | 2800 | 1.7616 | 0.6611 |
| 0.0473 | 137.93 | 3000 | 1.7885 | 0.6634 |
| 0.0535 | 147.13 | 3200 | 1.8877 | 0.6806 |
| 0.0468 | 156.32 | 3400 | 1.7766 | 0.6671 |
| 0.0386 | 165.52 | 3600 | 1.7956 | 0.6494 |
| 0.0418 | 174.71 | 3800 | 1.9402 | 0.6851 |
| 0.0426 | 183.91 | 4000 | 1.9777 | 0.6927 |
| 0.0395 | 193.1 | 4200 | 1.8733 | 0.6689 |
| 0.0392 | 202.3 | 4400 | 1.8994 | 0.6774 |
| 0.0377 | 211.49 | 4600 | 1.9983 | 0.6889 |
| 0.0354 | 220.69 | 4800 | 1.8858 | 0.6645 |
| 0.0315 | 229.89 | 5000 | 1.9716 | 0.6805 |
| 0.0312 | 239.08 | 5200 | 2.0422 | 0.6825 |
| 0.0292 | 248.28 | 5400 | 2.0780 | 0.7019 |
| 0.0283 | 257.47 | 5600 | 1.9102 | 0.6743 |
| 0.025 | 266.67 | 5800 | 1.9745 | 0.6756 |
| 0.0246 | 275.86 | 6000 | 2.1289 | 0.6918 |
| 0.0234 | 285.06 | 6200 | 2.1775 | 0.7068 |
| 0.0219 | 294.25 | 6400 | 2.1755 | 0.6935 |
| 0.0182 | 303.45 | 6600 | 2.1602 | 0.6764 |
| 0.0174 | 312.64 | 6800 | 2.1359 | 0.6596 |
| 0.0157 | 321.84 | 7000 | 2.1958 | 0.6797 |
| 0.0147 | 331.03 | 7200 | 2.1460 | 0.6657 |
| 0.0135 | 340.23 | 7400 | 2.2716 | 0.6719 |
| 0.0124 | 349.43 | 7600 | 2.3556 | 0.6762 |
| 0.0109 | 358.62 | 7800 | 2.2520 | 0.6632 |
| 0.0115 | 367.82 | 8000 | 2.3112 | 0.6802 |
| 0.0108 | 377.01 | 8200 | 2.2925 | 0.6659 |
| 0.0106 | 386.21 | 8400 | 2.2950 | 0.6726 |
| 0.0088 | 395.4 | 8600 | 2.3078 | 0.6735 |
| 0.0084 | 404.6 | 8800 | 2.3538 | 0.6723 |
| 0.0079 | 413.79 | 9000 | 2.3212 | 0.6615 |
| 0.0074 | 422.99 | 9200 | 2.3908 | 0.6774 |
| 0.0094 | 432.18 | 9400 | 2.3164 | 0.6779 |
| 0.0077 | 441.38 | 9600 | 2.3105 | 0.6649 |
| 0.0066 | 450.57 | 9800 | 2.3599 | 0.6742 |
| 0.007 | 459.77 | 10000 | 2.3675 | 0.6709 |
| 0.0056 | 468.97 | 10200 | 2.3964 | 0.6677 |
| 0.0049 | 478.16 | 10400 | 2.3858 | 0.6632 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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