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---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./800
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. -->
# ./800
This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 800 SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6191
- Wer Ortho: 30.5394
- Wer: 20.0215
## 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: 3e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 800
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 1.2835 | 2.0 | 100 | 0.7681 | 30.5758 | 19.3039 |
| 0.5883 | 4.0 | 200 | 0.6235 | 27.6968 | 17.5099 |
| 0.3246 | 6.0 | 300 | 0.5332 | 29.4461 | 19.6268 |
| 0.1851 | 8.0 | 400 | 0.5366 | 34.6574 | 23.3226 |
| 0.1133 | 10.0 | 500 | 0.5747 | 29.9198 | 19.0886 |
| 0.0837 | 12.0 | 600 | 0.5947 | 30.1020 | 19.9498 |
| 0.0697 | 14.0 | 700 | 0.6128 | 30.3571 | 20.4521 |
| 0.0622 | 16.0 | 800 | 0.6191 | 30.5394 | 20.0215 |
### Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1
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