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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-base-timit-demo-google-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-base-timit-demo-google-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: 0.6342
- Wer: 0.5808
## 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 9.1358 | 1.19 | 500 | 3.2710 | 1.0 |
| 3.0499 | 2.38 | 1000 | 1.8976 | 1.0 |
| 1.279 | 3.56 | 1500 | 0.7502 | 0.8228 |
| 0.7953 | 4.75 | 2000 | 0.5914 | 0.7343 |
| 0.6451 | 5.94 | 2500 | 0.6152 | 0.7280 |
| 0.5351 | 7.13 | 3000 | 0.5948 | 0.7041 |
| 0.4633 | 8.31 | 3500 | 0.5585 | 0.6712 |
| 0.4272 | 9.5 | 4000 | 0.5372 | 0.6457 |
| 0.3803 | 10.69 | 4500 | 0.5404 | 0.6402 |
| 0.3462 | 11.88 | 5000 | 0.5862 | 0.6484 |
| 0.3302 | 13.06 | 5500 | 0.5991 | 0.6426 |
| 0.3096 | 14.25 | 6000 | 0.5687 | 0.6287 |
| 0.2839 | 15.44 | 6500 | 0.5798 | 0.6384 |
| 0.2701 | 16.63 | 7000 | 0.5775 | 0.6047 |
| 0.2507 | 17.81 | 7500 | 0.5638 | 0.6065 |
| 0.2376 | 19.0 | 8000 | 0.5937 | 0.6094 |
| 0.2264 | 20.19 | 8500 | 0.5944 | 0.6065 |
| 0.2146 | 21.38 | 9000 | 0.6050 | 0.6122 |
| 0.1947 | 22.57 | 9500 | 0.6283 | 0.5992 |
| 0.1982 | 23.75 | 10000 | 0.6126 | 0.6018 |
| 0.1924 | 24.94 | 10500 | 0.6075 | 0.5962 |
| 0.1855 | 26.13 | 11000 | 0.6344 | 0.5938 |
| 0.1839 | 27.32 | 11500 | 0.6118 | 0.5880 |
| 0.1741 | 28.5 | 12000 | 0.6381 | 0.5878 |
| 0.1726 | 29.69 | 12500 | 0.6342 | 0.5808 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
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