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: 0.9159439626417611
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: 2.0166
- Wer: 0.9159
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: 80
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 12.6278 | 5.0 | 100 | 4.1583 | 1.0 |
| 4.0971 | 10.0 | 200 | 4.0317 | 1.0 |
| 3.9986 | 15.0 | 300 | 3.9758 | 1.0 |
| 3.7669 | 20.0 | 400 | 3.2290 | 1.0287 |
| 1.6097 | 25.0 | 500 | 1.8216 | 0.9860 |
| 0.5931 | 30.0 | 600 | 1.7982 | 0.9780 |
| 0.3501 | 35.0 | 700 | 1.9234 | 0.9867 |
| 0.2629 | 40.0 | 800 | 1.9051 | 0.9206 |
| 0.2055 | 45.0 | 900 | 1.9681 | 0.9246 |
| 0.1844 | 50.0 | 1000 | 2.0111 | 0.9393 |
| 0.1625 | 55.0 | 1100 | 2.0117 | 0.9286 |
| 0.1486 | 60.0 | 1200 | 2.0144 | 0.9326 |
| 0.1348 | 65.0 | 1300 | 2.0011 | 0.9373 |
| 0.1183 | 70.0 | 1400 | 2.0303 | 0.9053 |
| 0.1095 | 75.0 | 1500 | 2.0183 | 0.9239 |
| 0.1064 | 80.0 | 1600 | 2.0166 | 0.9159 |
Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1