metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-amharic-demo-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_16_1
type: common_voice_16_1
config: am
split: test
args: am
metrics:
- name: Wer
type: wer
value: 0.8639092728485657
wav2vec2-large-xls-r-300m-amharic-demo-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6333
- Wer: 0.8639
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: 100
- num_epochs: 60
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 12.6948 | 5.0 | 100 | 4.1621 | 1.0 |
| 4.1026 | 10.0 | 200 | 4.0365 | 1.0 |
| 4.0037 | 15.0 | 300 | 3.9726 | 1.0007 |
| 3.9485 | 20.0 | 400 | 3.9524 | 1.0007 |
| 3.4635 | 25.0 | 500 | 2.4384 | 0.9980 |
| 1.1709 | 30.0 | 600 | 1.6987 | 0.9453 |
| 0.4955 | 35.0 | 700 | 1.5927 | 0.9073 |
| 0.3163 | 40.0 | 800 | 1.6750 | 0.8833 |
| 0.2372 | 45.0 | 900 | 1.6683 | 0.8813 |
| 0.1896 | 50.0 | 1000 | 1.6555 | 0.8779 |
| 0.1619 | 55.0 | 1100 | 1.6312 | 0.8819 |
| 0.1473 | 60.0 | 1200 | 1.6333 | 0.8639 |
Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1