Abdulwahab Sahyoun
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---
license: apache-2.0
tags:
- automatic-speech-recognition
- abdusahmbzuai/arabic_speech_massive_300hrs
- generated_from_trainer
model-index:
- name: aradia-ctc-hubert-ft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# aradia-ctc-hubert-ft
This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on the ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_300HRS - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6946
- Wer: 0.3940
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.43 | 100 | 3.6934 | 1.0 |
| No log | 0.87 | 200 | 3.0763 | 1.0 |
| No log | 1.3 | 300 | 2.9737 | 1.0 |
| No log | 1.74 | 400 | 2.5734 | 1.0 |
| 5.0957 | 2.17 | 500 | 1.1900 | 0.9011 |
| 5.0957 | 2.61 | 600 | 0.9726 | 0.7572 |
| 5.0957 | 3.04 | 700 | 0.8960 | 0.6209 |
| 5.0957 | 3.48 | 800 | 0.7851 | 0.5515 |
| 5.0957 | 3.91 | 900 | 0.7271 | 0.5115 |
| 1.0312 | 4.35 | 1000 | 0.7053 | 0.4955 |
| 1.0312 | 4.78 | 1100 | 0.6823 | 0.4737 |
| 1.0312 | 5.22 | 1200 | 0.6768 | 0.4595 |
| 1.0312 | 5.65 | 1300 | 0.6635 | 0.4488 |
| 1.0312 | 6.09 | 1400 | 0.6602 | 0.4390 |
| 0.6815 | 6.52 | 1500 | 0.6464 | 0.4310 |
| 0.6815 | 6.95 | 1600 | 0.6455 | 0.4394 |
| 0.6815 | 7.39 | 1700 | 0.6630 | 0.4312 |
| 0.6815 | 7.82 | 1800 | 0.6521 | 0.4126 |
| 0.6815 | 8.26 | 1900 | 0.6282 | 0.4284 |
| 0.544 | 8.69 | 2000 | 0.6248 | 0.4178 |
| 0.544 | 9.13 | 2100 | 0.6510 | 0.4104 |
| 0.544 | 9.56 | 2200 | 0.6527 | 0.4013 |
| 0.544 | 10.0 | 2300 | 0.6511 | 0.4064 |
| 0.544 | 10.43 | 2400 | 0.6734 | 0.4061 |
| 0.4478 | 10.87 | 2500 | 0.6756 | 0.4145 |
| 0.4478 | 11.3 | 2600 | 0.6727 | 0.3990 |
| 0.4478 | 11.74 | 2700 | 0.6619 | 0.4007 |
| 0.4478 | 12.17 | 2800 | 0.6614 | 0.4019 |
| 0.4478 | 12.61 | 2900 | 0.6695 | 0.4004 |
| 0.3919 | 13.04 | 3000 | 0.6778 | 0.3966 |
| 0.3919 | 13.48 | 3100 | 0.6872 | 0.3971 |
| 0.3919 | 13.91 | 3200 | 0.6882 | 0.3945 |
| 0.3919 | 14.35 | 3300 | 0.6938 | 0.3937 |
| 0.3919 | 14.78 | 3400 | 0.6928 | 0.3946 |
### Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6