metadata
license: apache-2.0
tags:
- 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: fleurs
type: fleurs
config: ps_af
split: test
args: ps_af
metrics:
- name: Wer
type: wer
value: 0.5133015006821282
facebook/wav2vec2-xls-r-300m
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.9063
- Wer: 0.5133
- Cer: 0.1954
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
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 5.0767 | 6.33 | 500 | 4.8783 | 1.0 | 1.0 |
| 3.1156 | 12.66 | 1000 | 3.0990 | 1.0 | 1.0 |
| 1.3506 | 18.99 | 1500 | 1.1056 | 0.7031 | 0.2889 |
| 0.9997 | 25.32 | 2000 | 0.9191 | 0.5944 | 0.2301 |
| 0.7838 | 31.65 | 2500 | 0.8952 | 0.5556 | 0.2152 |
| 0.6665 | 37.97 | 3000 | 0.8908 | 0.5252 | 0.2017 |
| 0.6265 | 44.3 | 3500 | 0.9063 | 0.5133 | 0.1954 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2