File size: 2,327 Bytes
b55636d 9da3390 e45ca5d b55636d e45ca5d b55636d e45ca5d b55636d 9da3390 b55636d |
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 87 88 89 90 91 92 93 94 95 96 97 |
---
datasets:
- arbml/mgb2
license: apache-2.0
metrics:
- wer
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
model-index:
- name: Whisper Large V2 - Zaid Alyafeai
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: ar
metrics:
- type: wer
value: 38.23
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ar_eg
split: test
args: ar
metrics:
- type: wer
value: 11.6
name: Wer
---
<!-- 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. -->
# openai/whisper-large-v2
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8091
- Wer: 17.7875
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2528 | 0.2 | 2000 | 0.9370 | 22.1311 |
| 0.2718 | 0.4 | 4000 | 0.8721 | 24.9294 |
| 0.2745 | 0.6 | 6000 | 0.8770 | 20.5292 |
| 0.2157 | 0.8 | 8000 | 0.8774 | 18.1018 |
| 0.1729 | 1.0 | 10000 | 0.8091 | 17.7875 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|