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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: output
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 1.019918009027289
---
<!-- 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. -->
# output
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_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7883
- Wer: 1.0199
## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.92 | 0.95 | 400 | 2.9522 | 1.0026 |
| 1.0435 | 1.89 | 800 | 0.8608 | 1.0552 |
| 0.5354 | 2.84 | 1200 | 0.7762 | 1.0169 |
| 0.404 | 3.79 | 1600 | 0.6984 | 1.0293 |
| 0.3301 | 4.73 | 2000 | 0.6811 | 1.0217 |
| 0.2745 | 5.68 | 2400 | 0.7027 | 1.0308 |
| 0.2346 | 6.63 | 2800 | 0.7296 | 1.0185 |
| 0.2096 | 7.57 | 3200 | 0.7148 | 1.0294 |
| 0.1912 | 8.52 | 3600 | 0.7109 | 1.0335 |
| 0.172 | 9.47 | 4000 | 0.7894 | 1.0252 |
| 0.1567 | 10.41 | 4400 | 0.7592 | 1.0219 |
| 0.1457 | 11.36 | 4800 | 0.8030 | 1.0141 |
| 0.1337 | 12.31 | 5200 | 0.7811 | 1.0237 |
| 0.1288 | 13.25 | 5600 | 0.7703 | 1.0188 |
| 0.1165 | 14.2 | 6000 | 0.7728 | 1.0199 |
| 0.105 | 15.15 | 6400 | 0.7934 | 1.0206 |
| 0.1028 | 16.09 | 6800 | 0.7978 | 1.0185 |
| 0.092 | 17.04 | 7200 | 0.8276 | 1.0289 |
| 0.0901 | 17.99 | 7600 | 0.7881 | 1.0202 |
| 0.0818 | 18.93 | 8000 | 0.7847 | 1.0162 |
| 0.0801 | 19.88 | 8400 | 0.8142 | 1.0230 |
| 0.0768 | 20.83 | 8800 | 0.7735 | 1.0215 |
| 0.0721 | 21.78 | 9200 | 0.7941 | 1.0227 |
| 0.0658 | 22.72 | 9600 | 0.8100 | 1.0219 |
| 0.0627 | 23.67 | 10000 | 0.7592 | 1.0196 |
| 0.0591 | 24.62 | 10400 | 0.8028 | 1.0210 |
| 0.0537 | 25.56 | 10800 | 0.8019 | 1.0253 |
| 0.0507 | 26.51 | 11200 | 0.7951 | 1.0212 |
| 0.0495 | 27.46 | 11600 | 0.7893 | 1.0207 |
| 0.0466 | 28.4 | 12000 | 0.7854 | 1.0188 |
| 0.0431 | 29.35 | 12400 | 0.7883 | 1.0199 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.2.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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