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---
library_name: transformers
license: apache-2.0
base_model: shreyasdesaisuperU/whisper-medium-attempt2-1000-orders
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium 1000 orders Eleven Labs SSD superU
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 Medium 1000 orders Eleven Labs SSD superU
This model is a fine-tuned version of [shreyasdesaisuperU/whisper-medium-attempt2-1000-orders](https://huggingface.co/shreyasdesaisuperU/whisper-medium-attempt2-1000-orders) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0128
- Wer: 0.8606
## 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 OptimizerNames.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: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0668 | 0.4032 | 100 | 0.0388 | 17.3838 |
| 0.0142 | 0.8065 | 200 | 0.0061 | 11.3597 |
| 0.0075 | 1.2097 | 300 | 0.0075 | 9.6386 |
| 0.0073 | 1.6129 | 400 | 0.0104 | 7.7453 |
| 0.0087 | 2.0161 | 500 | 0.0125 | 2.9260 |
| 0.0046 | 2.4194 | 600 | 0.0080 | 1.5491 |
| 0.0087 | 2.8226 | 700 | 0.0039 | 1.7212 |
| 0.0066 | 3.2258 | 800 | 0.0042 | 1.3769 |
| 0.0032 | 3.6290 | 900 | 0.0095 | 1.0327 |
| 0.0027 | 4.0323 | 1000 | 0.0114 | 1.5491 |
| 0.0021 | 4.4355 | 1100 | 0.0099 | 1.7212 |
| 0.0039 | 4.8387 | 1200 | 0.0121 | 1.8933 |
| 0.0017 | 5.2419 | 1300 | 0.0126 | 1.3769 |
| 0.0033 | 5.6452 | 1400 | 0.0093 | 1.8933 |
| 0.0037 | 6.0484 | 1500 | 0.0126 | 1.2048 |
| 0.0013 | 6.4516 | 1600 | 0.0090 | 1.2048 |
| 0.0014 | 6.8548 | 1700 | 0.0102 | 1.2048 |
| 0.0002 | 7.2581 | 1800 | 0.0115 | 0.8606 |
| 0.0005 | 7.6613 | 1900 | 0.0142 | 1.0327 |
| 0.0002 | 8.0645 | 2000 | 0.0128 | 0.8606 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.2.2+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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