metadata
library_name: transformers
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-large-xlsr-53-arabic
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-fine-tuning_23_colab
results: []
wav2vec2-base-fine-tuning_23_colab
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-arabic on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7692
- Wer: 0.5937
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
40.2869 | 1.3333 | 250 | 3.3969 | 1.0 |
3.314 | 2.6667 | 500 | 2.9060 | 1.0 |
1.7031 | 4.0 | 750 | 1.1416 | 0.7329 |
0.8774 | 5.3333 | 1000 | 0.8753 | 0.6403 |
0.6796 | 6.6667 | 1250 | 0.8064 | 0.6110 |
0.5698 | 8.0 | 1500 | 0.7932 | 0.6147 |
0.4989 | 9.3333 | 1750 | 0.7692 | 0.5937 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3