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---
license: apache-2.0
language:
- gn
tags:
- generated_from_trainer
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- hf-asr-leaderboard
datasets:
- common_voice
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-base-gn-demo
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-gn-demo
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7426
- Wer: 0.7256
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 50
- num_epochs: 60
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 4.0 | 100 | 0.7045 | 0.7409 |
| No log | 8.0 | 200 | 0.7200 | 0.75 |
| No log | 12.0 | 300 | 0.7400 | 0.7439 |
| No log | 16.0 | 400 | 0.7677 | 0.7515 |
| 0.0846 | 20.0 | 500 | 0.7765 | 0.7271 |
| 0.0846 | 24.0 | 600 | 0.7821 | 0.7287 |
| 0.0846 | 28.0 | 700 | 0.7671 | 0.7180 |
| 0.0846 | 32.0 | 800 | 0.7594 | 0.7180 |
| 0.0846 | 36.0 | 900 | 0.7500 | 0.7165 |
| 0.0713 | 40.0 | 1000 | 0.7351 | 0.7287 |
| 0.0713 | 44.0 | 1100 | 0.7361 | 0.7241 |
| 0.0713 | 48.0 | 1200 | 0.7389 | 0.7378 |
| 0.0713 | 52.0 | 1300 | 0.7424 | 0.7210 |
| 0.0713 | 56.0 | 1400 | 0.7425 | 0.7256 |
| 0.0669 | 60.0 | 1500 | 0.7426 | 0.7256 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3
|