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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_9_0
metrics:
- wer
model-index:
- name: cv9-special-batch12-lr4-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_9_0
type: common_voice_9_0
config: id
split: train
args: id
metrics:
- name: Wer
type: wer
value: 0.3947650718729886
---
<!-- 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. -->
# cv9-special-batch12-lr4-small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_9_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Wer: 0.3948
## 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: 0.0001
- train_batch_size: 12
- eval_batch_size: 6
- 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: 5000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2264 | 2.38 | 1000 | 0.1836 | 14.9989 |
| 0.0873 | 4.75 | 2000 | 0.0633 | 5.0869 |
| 0.0236 | 7.13 | 3000 | 0.0262 | 1.8086 |
| 0.0068 | 9.5 | 4000 | 0.0062 | 0.6222 |
| 0.0002 | 11.88 | 5000 | 0.0004 | 0.3948 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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