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-53-Hindi-Version1
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: fleurs
type: fleurs
config: hi_in
split: None
args: hi_in
metrics:
- type: wer
value: 0.5457385531582544
name: Wer
wav2vec2-large-xlsr-53-Hindi-Version1
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: 0.7287
- Wer: 0.5457
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: 3e-05
- 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: 70
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.6017 | 6.7568 | 500 | 3.5280 | 1.0 |
| 3.3879 | 13.5135 | 1000 | 3.3755 | 1.0 |
| 3.3566 | 20.2703 | 1500 | 3.3544 | 1.0 |
| 3.3133 | 27.0270 | 2000 | 3.2753 | 1.0 |
| 2.216 | 33.7838 | 2500 | 1.8757 | 0.9159 |
| 1.2972 | 40.5405 | 3000 | 1.0386 | 0.6969 |
| 1.0939 | 47.2973 | 3500 | 0.8590 | 0.6190 |
| 1.0188 | 54.0541 | 4000 | 0.7791 | 0.5797 |
| 0.9468 | 60.8108 | 4500 | 0.7461 | 0.5575 |
| 0.9806 | 67.5676 | 5000 | 0.7287 | 0.5457 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1