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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- wwwtwwwt/fineaudio-Entertainment
metrics:
- wer
model-index:
- name: Whisper Tiny En - Entertainment - Game Commentary
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fineaudio-Entertainment-Game Commentary
type: wwwtwwwt/fineaudio-Entertainment
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 46.31946283631152
---
<!-- 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 Tiny En - Entertainment - Game Commentary
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fineaudio-Entertainment-Game Commentary dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8817
- Wer: 46.3195
## 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: 8
- seed: 42
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.8341 | 0.5984 | 1000 | 0.9697 | 53.8799 |
| 0.6267 | 1.1969 | 2000 | 0.9055 | 49.3543 |
| 0.6058 | 1.7953 | 3000 | 0.8844 | 47.1311 |
| 0.5022 | 2.3938 | 4000 | 0.8817 | 46.3195 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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