File size: 3,575 Bytes
fc3ff93 34323cb 75e4ae6 34323cb 75e4ae6 fc3ff93 34323cb fc3ff93 34323cb fc3ff93 75e4ae6 fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 34323cb fc3ff93 75e4ae6 34323cb fc3ff93 34323cb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
datasets:
- common_voice_14_0
metrics:
- wer
model-index:
- name: XLS-R-LUGANDA-ASR-CV-14-1B
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_14_0
type: common_voice_14_0
config: lg
split: test
args: lg
metrics:
- name: Wer
type: wer
value: 0.30603965548369283
---
<!-- 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. -->
# XLS-R-LUGANDA-ASR-CV-14-1B
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_14_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.3060
- Cer: 0.0713
## 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 1.5535 | 0.18 | 400 | 0.1685 | inf | 0.6590 |
| 0.539 | 0.36 | 800 | 0.1516 | inf | 0.5934 |
| 0.49 | 0.54 | 1200 | 0.1365 | inf | 0.5466 |
| 0.4569 | 0.72 | 1600 | 0.1364 | inf | 0.5523 |
| 0.4845 | 0.45 | 2000 | 0.1525 | inf | 0.5907 |
| 0.4592 | 0.54 | 2400 | 0.1485 | inf | 0.5766 |
| 0.4447 | 0.63 | 2800 | 0.1397 | inf | 0.5482 |
| 0.426 | 0.72 | 3200 | 0.1352 | inf | 0.5290 |
| 0.4454 | 0.81 | 3600 | inf | 0.5330 | 0.1333 |
| 0.4188 | 0.9 | 4000 | inf | 0.4903 | 0.1240 |
| 0.4083 | 0.99 | 4400 | inf | 0.4857 | 0.1226 |
| 0.367 | 1.08 | 4800 | inf | 0.4499 | 0.1114 |
| 0.3468 | 1.17 | 5200 | inf | 0.4345 | 0.1063 |
| 0.3401 | 1.27 | 5600 | inf | 0.4130 | 0.1009 |
| 0.3269 | 1.36 | 6000 | inf | 0.4113 | 0.1004 |
| 0.3171 | 1.45 | 6400 | inf | 0.3934 | 0.0956 |
| 0.2996 | 1.54 | 6800 | inf | 0.3803 | 0.0913 |
| 0.288 | 1.63 | 7200 | inf | 0.3681 | 0.0891 |
| 0.2812 | 1.72 | 7600 | inf | 0.3573 | 0.0853 |
| 0.2699 | 1.81 | 8000 | inf | 0.3504 | 0.0835 |
| 0.2584 | 1.9 | 8400 | inf | 0.3343 | 0.0786 |
| 0.2424 | 1.99 | 8800 | inf | 0.3232 | 0.0759 |
| 0.2201 | 2.08 | 9200 | inf | 0.3176 | 0.0740 |
| 0.2031 | 2.17 | 9600 | inf | 0.3085 | 0.0719 |
| 0.2007 | 2.26 | 10000 | inf | 0.3060 | 0.0713 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.0
- Tokenizers 0.15.2
|