metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- google/fleurs
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-en-finetune
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: GOOGLE/FLEURS - EN_US
type: fleurs
config: en_us
split: test
args: 'Config: en_us, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 0.25982311149775267
wav2vec2-common_voice-en-finetune
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the GOOGLE/FLEURS - EN_US dataset. It achieves the following results on the evaluation set:
- Loss: 0.3436
- Wer: 0.2598
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: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0870 | 100 | 3.5106 | 1.0 |
| No log | 2.1739 | 200 | 2.9226 | 1.0 |
| No log | 3.2609 | 300 | 2.8745 | 1.0 |
| No log | 4.3478 | 400 | 1.8100 | 0.9804 |
| 3.7609 | 5.4348 | 500 | 0.4771 | 0.4207 |
| 3.7609 | 6.5217 | 600 | 0.3808 | 0.3484 |
| 3.7609 | 7.6087 | 700 | 0.3408 | 0.2872 |
| 3.7609 | 8.6957 | 800 | 0.3479 | 0.2719 |
| 3.7609 | 9.7826 | 900 | 0.3437 | 0.2604 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1