metadata
license: apache-2.0
tags:
- automatic-speech-recognition
- google/fleurs
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: facebook/wav2vec2-xls-r-300m
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: GOOGLE/FLEURS - PS_AF
type: fleurs
config: ps_af
split: test
args: 'Config: ps_af, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 0.5156036834924966
facebook/wav2vec2-xls-r-300m
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/FLEURS - PS_AF dataset. It achieves the following results on the evaluation set:
- Loss: 0.9162
- Wer: 0.5156
- Cer: 0.1969
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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- training_steps: 4500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 5.0767 | 6.33 | 500 | 1.0 | 4.8783 | 1.0 |
| 3.1156 | 12.66 | 1000 | 1.0 | 3.0990 | 1.0 |
| 1.3506 | 18.99 | 1500 | 0.2889 | 1.1056 | 0.7031 |
| 0.9997 | 25.32 | 2000 | 0.2301 | 0.9191 | 0.5944 |
| 0.7838 | 31.65 | 2500 | 0.2152 | 0.8952 | 0.5556 |
| 0.6665 | 37.97 | 3000 | 0.2017 | 0.8908 | 0.5252 |
| 0.6265 | 44.3 | 3500 | 0.1954 | 0.9063 | 0.5133 |
| 0.5935 | 50.63 | 4000 | 0.1969 | 0.9162 | 0.5156 |
| 0.5174 | 56.96 | 4500 | 0.9287 | 0.5140 | 0.1972 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2