File size: 2,163 Bytes
1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 5f4750d 1b392e5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
---
language:
- ur
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Large-v2 Urdu
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ur
type: mozilla-foundation/common_voice_11_0
config: ur
split: test
args: ur
metrics:
- name: Wer
type: wer
value: 23.5020721174329
---
<!-- 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 Large-v2 Urdu
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 ur dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5947
- Wer: 23.5021
## 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: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- 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: 100
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1935 | 1.1 | 200 | 0.4241 | 29.6526 |
| 0.0649 | 3.09 | 400 | 0.4683 | 26.0622 |
| 0.0156 | 5.08 | 600 | 0.5444 | 25.8104 |
| 0.0039 | 7.08 | 800 | 0.5947 | 23.5021 |
| 0.0019 | 9.07 | 1000 | 0.6123 | 23.8933 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|