metadata
library_name: transformers
language:
- sn
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- DigitalUmuganda/Afrivoice
metrics:
- wer
model-index:
- name: facebook/wav2vec2-xls-r-300m
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Afrivoice
type: DigitalUmuganda/Afrivoice
metrics:
- name: Wer
type: wer
value: 0.3289275474998785
facebook/wav2vec2-xls-r-300m
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the Afrivoice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3536
- Wer: 0.3289
- Cer: 0.0684
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.8923 | 1.0 | 1885 | 0.3250 | 0.4671 | 0.0874 |
| 0.2338 | 2.0 | 3770 | 0.2228 | 0.3238 | 0.0547 |
| 0.1887 | 3.0 | 5655 | 0.2019 | 0.2795 | 0.0479 |
| 0.1641 | 4.0 | 7540 | 0.1987 | 0.2836 | 0.0493 |
| 0.1445 | 5.0 | 9425 | 0.1932 | 0.2673 | 0.0455 |
| 0.1251 | 6.0 | 11310 | 0.1969 | 0.2710 | 0.0457 |
| 0.1082 | 7.0 | 13195 | 0.2057 | 0.2623 | 0.0441 |
| 0.0929 | 8.0 | 15080 | 0.2181 | 0.2676 | 0.0451 |
| 0.0796 | 9.0 | 16965 | 0.2352 | 0.2678 | 0.0448 |
| 0.0671 | 10.0 | 18850 | 0.2427 | 0.2725 | 0.0460 |
| 0.0575 | 11.0 | 20735 | 0.2593 | 0.2709 | 0.0451 |
| 0.0492 | 12.0 | 22620 | 0.2744 | 0.2789 | 0.0460 |
| 0.0427 | 13.0 | 24505 | 0.2792 | 0.2763 | 0.0456 |
| 0.0389 | 14.0 | 26390 | 0.2831 | 0.2871 | 0.0461 |
| 0.034 | 15.0 | 28275 | 0.2987 | 0.2734 | 0.0446 |
| 0.0322 | 16.0 | 30160 | 0.3052 | 0.2806 | 0.0450 |
| 0.0298 | 17.0 | 32045 | 0.3148 | 0.2713 | 0.0443 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.2.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1