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---
language:
- ar
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium - Karthik Avinash
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 39.473684210526315
---
<!-- 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. -->
# Whisper Medium - Karthik Avinash
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4340
- Wer: 39.4737
## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- 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
- training_steps: 800
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.0267 | 0.0166 | 20 | 1.1833 | 47.3684 |
| 0.7014 | 0.0333 | 40 | 0.9320 | 40.7895 |
| 0.5484 | 0.0499 | 60 | 0.6066 | 50.0 |
| 0.3202 | 0.0665 | 80 | 0.5057 | 56.5789 |
| 0.3791 | 0.0832 | 100 | 0.4702 | 47.3684 |
| 0.3701 | 0.0998 | 120 | 0.4606 | 46.0526 |
| 0.3584 | 0.1164 | 140 | 0.4618 | 47.3684 |
| 0.3459 | 0.1330 | 160 | 0.4809 | 51.3158 |
| 0.2758 | 0.1497 | 180 | 0.4729 | 52.6316 |
| 0.3636 | 0.1663 | 200 | 0.4597 | 48.6842 |
| 0.3649 | 0.1829 | 220 | 0.4475 | 43.4211 |
| 0.325 | 0.1996 | 240 | 0.4642 | 43.4211 |
| 0.3052 | 0.2162 | 260 | 0.4800 | 51.3158 |
| 0.1836 | 0.2328 | 280 | 0.4854 | 46.0526 |
| 0.2539 | 0.2495 | 300 | 0.4735 | 55.2632 |
| 0.3174 | 0.2661 | 320 | 0.4748 | 44.7368 |
| 0.3184 | 0.2827 | 340 | 0.4545 | 44.7368 |
| 0.2216 | 0.2994 | 360 | 0.4711 | 39.4737 |
| 0.2849 | 0.3160 | 380 | 0.4219 | 36.8421 |
| 0.2108 | 0.3326 | 400 | 0.4382 | 39.4737 |
| 0.2431 | 0.3493 | 420 | 0.4622 | 35.5263 |
| 0.2776 | 0.3659 | 440 | 0.4265 | 42.1053 |
| 0.3011 | 0.3825 | 460 | 0.4400 | 35.5263 |
| 0.2659 | 0.3991 | 480 | 0.5303 | 46.0526 |
| 0.3692 | 0.4158 | 500 | 0.4142 | 38.1579 |
| 0.3166 | 0.4324 | 520 | 0.4278 | 38.1579 |
| 0.2855 | 0.4490 | 540 | 0.4518 | 38.1579 |
| 0.2286 | 0.4657 | 560 | 0.4679 | 48.6842 |
| 0.2136 | 0.4823 | 580 | 0.4749 | 40.7895 |
| 0.2503 | 0.4989 | 600 | 0.4740 | 34.2105 |
| 0.1904 | 0.5156 | 620 | 0.4547 | 39.4737 |
| 0.376 | 0.5322 | 640 | 0.4272 | 40.7895 |
| 0.24 | 0.5488 | 660 | 0.4594 | 40.7895 |
| 0.2928 | 0.5655 | 680 | 0.4498 | 40.7895 |
| 0.2473 | 0.5821 | 700 | 0.4432 | 43.4211 |
| 0.5217 | 0.5987 | 720 | 0.4481 | 40.7895 |
| 0.1973 | 0.6154 | 740 | 0.4381 | 43.4211 |
| 0.272 | 0.6320 | 760 | 0.4407 | 39.4737 |
| 0.2364 | 0.6486 | 780 | 0.4345 | 40.7895 |
| 0.194 | 0.6652 | 800 | 0.4340 | 39.4737 |
### Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.4.0+cu124
- Datasets 2.20.0
- Tokenizers 0.19.1
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