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---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-hi
results: []
---
<!-- 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-small-hi
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: 0.0000
- Wer: 33.6364
## 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: 8
- eval_batch_size: 8
- 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: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4926 | 25.0 | 100 | 0.1674 | 57.5758 |
| 0.0002 | 50.0 | 200 | 0.0001 | 3.9394 |
| 0.0001 | 75.0 | 300 | 0.0001 | 5.1515 |
| 0.0001 | 100.0 | 400 | 0.0001 | 10.3030 |
| 0.0001 | 125.0 | 500 | 0.0001 | 11.5152 |
| 0.0 | 150.0 | 600 | 0.0000 | 28.4848 |
| 0.0 | 175.0 | 700 | 0.0000 | 30.0 |
| 0.0 | 200.0 | 800 | 0.0000 | 29.0909 |
| 0.0 | 225.0 | 900 | 0.0000 | 33.6364 |
| 0.0 | 250.0 | 1000 | 0.0000 | 33.6364 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.19.1
- Tokenizers 0.19.1
|