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---
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: whisper-medium-mediaspeech-cv-tr
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 tr
type: mozilla-foundation/common_voice_11_0
config: tr
split: test
args: tr
metrics:
- type: wer
value: 9.9776
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. -->
# whisper-medium-mediaspeech-cv-tr
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1813
- Wer: 9.9776
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1187 | 0.33 | 1000 | 0.2169 | 13.7678 |
| 0.0579 | 1.26 | 2000 | 0.1814 | 10.8222 |
| 0.0313 | 2.19 | 3000 | 0.1813 | 9.9776 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|