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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xlsr-53-demo-colab
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-xlsr-53-demo-colab
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7860
- Wer: 1.1067
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 8.2273 | 44.42 | 400 | 3.3544 | 1.0 |
| 0.9228 | 88.84 | 800 | 4.7054 | 1.1601 |
| 0.1423 | 133.32 | 1200 | 5.9489 | 1.1578 |
| 0.0751 | 177.74 | 1600 | 5.5939 | 1.1717 |
| 0.0554 | 222.21 | 2000 | 6.1230 | 1.1717 |
| 0.0356 | 266.63 | 2400 | 6.2845 | 1.1613 |
| 0.0288 | 311.11 | 2800 | 6.6109 | 1.2100 |
| 0.0223 | 355.53 | 3200 | 6.5605 | 1.1299 |
| 0.0197 | 399.95 | 3600 | 7.1242 | 1.1682 |
| 0.0171 | 444.42 | 4000 | 7.2452 | 1.1578 |
| 0.0149 | 488.84 | 4400 | 7.4048 | 1.0684 |
| 0.0118 | 533.32 | 4800 | 6.6227 | 1.1172 |
| 0.011 | 577.74 | 5200 | 6.7909 | 1.1566 |
| 0.0095 | 622.21 | 5600 | 6.8088 | 1.1102 |
| 0.0077 | 666.63 | 6000 | 7.4451 | 1.1311 |
| 0.0062 | 711.11 | 6400 | 6.8486 | 1.0777 |
| 0.0051 | 755.53 | 6800 | 6.8812 | 1.1241 |
| 0.0051 | 799.95 | 7200 | 6.9987 | 1.1450 |
| 0.0041 | 844.42 | 7600 | 7.3048 | 1.1323 |
| 0.0044 | 888.84 | 8000 | 6.6644 | 1.1125 |
| 0.0031 | 933.32 | 8400 | 6.6298 | 1.1148 |
| 0.0027 | 977.74 | 8800 | 6.7860 | 1.1067 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
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