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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-grain
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-xls-r-300m-grain
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the Grain gender-balanced dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1510
- Wer: 0.0762
## 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: 32
- 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: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.1496 | 2.5 | 400 | 0.7656 | 0.8096 |
| 0.2914 | 5.0 | 800 | 0.3202 | 0.3544 |
| 0.1152 | 7.5 | 1200 | 0.2666 | 0.2894 |
| 0.0722 | 10.0 | 1600 | 0.2834 | 0.2458 |
| 0.0528 | 12.5 | 2000 | 0.2475 | 0.2159 |
| 0.0423 | 15.0 | 2400 | 0.2430 | 0.1971 |
| 0.0334 | 17.5 | 2800 | 0.2250 | 0.1925 |
| 0.0288 | 20.0 | 3200 | 0.2119 | 0.1779 |
| 0.0253 | 22.5 | 3600 | 0.2226 | 0.1711 |
| 0.0214 | 25.0 | 4000 | 0.2224 | 0.1685 |
| 0.0217 | 27.5 | 4400 | 0.2098 | 0.1516 |
| 0.0182 | 30.0 | 4800 | 0.2153 | 0.1716 |
| 0.0173 | 32.5 | 5200 | 0.1925 | 0.1451 |
| 0.0137 | 35.0 | 5600 | 0.2241 | 0.1469 |
| 0.0118 | 37.5 | 6000 | 0.2013 | 0.1515 |
| 0.0133 | 40.0 | 6400 | 0.1990 | 0.1332 |
| 0.0125 | 42.5 | 6800 | 0.2146 | 0.1502 |
| 0.0103 | 45.0 | 7200 | 0.2191 | 0.1317 |
| 0.0089 | 47.5 | 7600 | 0.1869 | 0.1246 |
| 0.0091 | 50.0 | 8000 | 0.1734 | 0.1251 |
| 0.008 | 52.5 | 8400 | 0.2008 | 0.1290 |
| 0.0071 | 55.0 | 8800 | 0.1828 | 0.1260 |
| 0.0064 | 57.5 | 9200 | 0.1689 | 0.1081 |
| 0.0061 | 60.0 | 9600 | 0.1676 | 0.1111 |
| 0.0051 | 62.5 | 10000 | 0.1707 | 0.1048 |
| 0.0056 | 65.0 | 10400 | 0.1741 | 0.1131 |
| 0.0046 | 67.5 | 10800 | 0.1836 | 0.1034 |
| 0.0036 | 70.0 | 11200 | 0.1655 | 0.0966 |
| 0.0037 | 72.5 | 11600 | 0.1734 | 0.1047 |
| 0.003 | 75.0 | 12000 | 0.1718 | 0.0975 |
| 0.0032 | 77.5 | 12400 | 0.1598 | 0.0986 |
| 0.0023 | 80.0 | 12800 | 0.1640 | 0.0966 |
| 0.0019 | 82.5 | 13200 | 0.1701 | 0.0862 |
| 0.0015 | 85.0 | 13600 | 0.1643 | 0.0854 |
| 0.0016 | 87.5 | 14000 | 0.1470 | 0.0823 |
| 0.0014 | 90.0 | 14400 | 0.1589 | 0.0838 |
| 0.0011 | 92.5 | 14800 | 0.1610 | 0.0834 |
| 0.0013 | 95.0 | 15200 | 0.1457 | 0.0788 |
| 0.001 | 97.5 | 15600 | 0.1537 | 0.0762 |
| 0.001 | 100.0 | 16000 | 0.1510 | 0.0762 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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