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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: results
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ne-NP
split: validated+other
args: ne-NP
metrics:
- name: Wer
type: wer
value: 0.5865921787709497
---
<!-- 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. -->
# results
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_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7289
- Wer: 0.5866
## 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: 200
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.4919 | 2.9851 | 100 | 1.2236 | 0.9106 |
| 1.0086 | 5.9701 | 200 | 0.9436 | 0.8291 |
| 0.6072 | 8.9552 | 300 | 0.8277 | 0.7117 |
| 0.55 | 11.9403 | 400 | 0.7774 | 0.6726 |
| 0.3398 | 14.9254 | 500 | 0.7344 | 0.6212 |
| 0.2543 | 17.9104 | 600 | 0.7368 | 0.6212 |
| 0.3558 | 20.8955 | 700 | 0.7313 | 0.5788 |
| 0.1751 | 23.8806 | 800 | 0.7060 | 0.5855 |
| 0.1502 | 26.8657 | 900 | 0.7289 | 0.5866 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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