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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-large-v2
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_myst
type: rishabhjain16/infer_myst
config: en
split: test
metrics:
- type: wer
value: 11.62
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_pfs
type: rishabhjain16/infer_pfs
config: en
split: test
metrics:
- type: wer
value: 2.84
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_cmu
type: rishabhjain16/infer_cmu
config: en
split: test
metrics:
- type: wer
value: 1.75
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/libritts_dev_clean
type: rishabhjain16/libritts_dev_clean
config: en
split: test
metrics:
- type: wer
value: 4.53
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_pf_swedish
type: rishabhjain16/infer_pf_swedish
config: en
split: test
metrics:
- type: wer
value: 8.36
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_pf_german
type: rishabhjain16/infer_pf_german
config: en
split: test
metrics:
- type: wer
value: 34.26
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_pf_italian
type: rishabhjain16/infer_pf_italian
config: en
split: test
metrics:
- type: wer
value: 4.4
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_so_chinese
type: rishabhjain16/infer_so_chinese
config: en
split: test
metrics:
- type: wer
value: 14.52
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: 0.1969
- Wer: 9.3970
## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6144 | 0.12 | 500 | 0.2795 | 14.0737 |
| 0.1643 | 0.25 | 1000 | 0.2213 | 11.4916 |
| 0.2175 | 0.38 | 1500 | 0.2009 | 10.0021 |
| 0.1512 | 1.11 | 2000 | 0.1980 | 11.2632 |
| 0.1527 | 1.24 | 2500 | 0.1916 | 10.8469 |
| 0.0918 | 1.36 | 3000 | 0.1890 | 9.6498 |
| 0.047 | 2.1 | 3500 | 0.2034 | 9.4274 |
| 0.0822 | 2.23 | 4000 | 0.1969 | 9.3970 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
|