metadata
license: apache-2.0
tags:
- generated_from_trainer
base_model: Amadkour/wav2vec2-large-xls-r-300m-tr-softkour
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-tr-softkour
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: ar
split: test
args: ar
metrics:
- type: wer
value: 0.44904159531569354
name: Wer
wav2vec2-large-xls-r-300m-tr-softkour
This model is a fine-tuned version of Amadkour/wav2vec2-large-xls-r-300m-tr-softkour on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4793
- Wer: 0.4490
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4662 | 0.33 | 400 | 0.7627 | 0.6241 |
| 0.3927 | 0.67 | 800 | 0.7286 | 0.6213 |
| 0.4613 | 1.0 | 1200 | 0.5779 | 0.5185 |
| 0.4552 | 1.33 | 1600 | 0.5412 | 0.4945 |
| 0.4145 | 1.66 | 2000 | 0.4922 | 0.4652 |
| 0.3713 | 2.0 | 2400 | 0.4793 | 0.4490 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2