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---
tags:
- generated_from_trainer
datasets:
- evanarlian/common_voice_11_0_id_filtered
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-164m-id
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: evanarlian/common_voice_11_0_id_filtered
type: evanarlian/common_voice_11_0_id_filtered
metrics:
- name: Wer
type: wer
value: 0.2923162069919749
---
<!-- 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-xls-r-164m-id
This model is a fine-tuned version of [evanarlian/distil-wav2vec2-xls-r-164m-id](https://huggingface.co/evanarlian/distil-wav2vec2-xls-r-164m-id) on the evanarlian/common_voice_11_0_id_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2865
- Wer: 0.2923
## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 80.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.4047 | 4.59 | 5000 | 1.0167 | 0.9138 |
| 0.587 | 9.18 | 10000 | 0.4639 | 0.5615 |
| 0.3782 | 13.77 | 15000 | 0.3375 | 0.4496 |
| 0.2867 | 18.37 | 20000 | 0.2881 | 0.4022 |
| 0.2519 | 22.96 | 25000 | 0.2775 | 0.3700 |
| 0.1941 | 27.55 | 30000 | 0.2701 | 0.3516 |
| 0.1727 | 32.14 | 35000 | 0.2795 | 0.3486 |
| 0.1448 | 36.73 | 40000 | 0.2878 | 0.3364 |
| 0.1251 | 41.32 | 45000 | 0.2649 | 0.3275 |
| 0.113 | 45.91 | 50000 | 0.2862 | 0.3168 |
| 0.0994 | 50.51 | 55000 | 0.2798 | 0.3091 |
| 0.0938 | 55.1 | 60000 | 0.2864 | 0.3070 |
| 0.0853 | 59.69 | 65000 | 0.2860 | 0.3069 |
| 0.0724 | 64.28 | 70000 | 0.2994 | 0.3003 |
| 0.0723 | 68.87 | 75000 | 0.2951 | 0.2983 |
| 0.0666 | 73.46 | 80000 | 0.2886 | 0.2941 |
| 0.0659 | 78.05 | 85000 | 0.2865 | 0.2923 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
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