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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- lalipa/jv_id_asr_split
metrics:
- wer
model-index:
- name: hyperparameter
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: lalipa/jv_id_asr_split jv_id_asr_source
type: lalipa/jv_id_asr_split
config: jv_id_asr_source
split: validation
args: jv_id_asr_source
metrics:
- name: Wer
type: wer
value: 0.6883827458964245
---
<!-- 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. -->
# hyperparameter
This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the lalipa/jv_id_asr_split jv_id_asr_source dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4506
- Wer: 0.6884
- Cer: 0.2050
## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.9694 | 0.1020 | 30 | 3.7782 | 1.8748 | 1.0887 |
| 3.3735 | 0.2041 | 60 | 2.9598 | 1.0019 | 0.4254 |
| 2.5449 | 0.3061 | 90 | 2.1989 | 0.8820 | 0.3221 |
| 1.9987 | 0.4082 | 120 | 1.8648 | 0.8004 | 0.2606 |
| 1.7671 | 0.5102 | 150 | 1.6909 | 0.7619 | 0.2312 |
| 1.6285 | 0.6122 | 180 | 1.5863 | 0.7336 | 0.2245 |
| 1.5475 | 0.7143 | 210 | 1.5251 | 0.7216 | 0.2213 |
| 1.4793 | 0.8163 | 240 | 1.4807 | 0.6942 | 0.2035 |
| 1.5013 | 0.9184 | 270 | 1.4582 | 0.6904 | 0.2057 |
| 1.4438 | 1.0204 | 300 | 1.4506 | 0.6884 | 0.2050 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1
- Datasets 3.0.1
- Tokenizers 0.20.0
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