metadata
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- fleurs
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-oria-v0
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: fleurs
type: fleurs
config: or_in
split: None
args: or_in
metrics:
- type: wer
value: 0.4972150445018662
name: Wer
wav2vec2-large-xlsr-oria-v0
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.6050
- Wer: 0.4972
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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.6722 | 2.1505 | 100 | 5.4667 | 1.0 |
| 3.4956 | 4.3011 | 200 | 3.4905 | 1.0 |
| 3.4526 | 6.4516 | 300 | 3.4624 | 1.0 |
| 3.4548 | 8.6022 | 400 | 3.4494 | 1.0 |
| 3.4352 | 10.7527 | 500 | 3.4267 | 1.0 |
| 3.0335 | 12.9032 | 600 | 2.8300 | 1.0 |
| 1.021 | 15.0538 | 700 | 0.9941 | 0.7938 |
| 0.6175 | 17.2043 | 800 | 0.7318 | 0.6385 |
| 0.5257 | 19.3548 | 900 | 0.6485 | 0.5820 |
| 0.4232 | 21.5054 | 1000 | 0.6105 | 0.5430 |
| 0.3202 | 23.6559 | 1100 | 0.5906 | 0.5192 |
| 0.2767 | 25.8065 | 1200 | 0.6025 | 0.5079 |
| 0.2679 | 27.9570 | 1300 | 0.6050 | 0.4972 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1