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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
- precision
- recall
- f1
model-index:
- name: ./whisper-medium-ea_5hr_v2
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-ea_5hr_v2
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Afrispeech-200 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4999
- Wer Ortho: 0.2185
- Wer: 0.1579
- Cer: 0.0705
- Precision: 0.9097
- Recall: 0.9048
- F1: 0.9068
## 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | Cer | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|:------:|:------:|
| 0.5036 | 0.1179 | 50 | 0.6665 | 0.2366 | 0.1752 | 0.0784 | 0.9011 | 0.8964 | 0.8982 |
| 0.5931 | 0.2358 | 100 | 0.5603 | 0.2211 | 0.1622 | 0.0689 | 0.9073 | 0.9022 | 0.9043 |
| 0.5468 | 0.3538 | 150 | 0.5329 | 0.2344 | 0.1807 | 0.0911 | 0.9033 | 0.8938 | 0.8974 |
| 0.5159 | 0.4717 | 200 | 0.5213 | 0.2247 | 0.1675 | 0.0814 | 0.9084 | 0.9044 | 0.9058 |
| 0.4744 | 0.5896 | 250 | 0.5160 | 0.2332 | 0.1703 | 0.0805 | 0.9064 | 0.8987 | 0.9016 |
| 0.4753 | 0.7075 | 300 | 0.5132 | 0.2116 | 0.1536 | 0.0661 | 0.9097 | 0.9061 | 0.9074 |
| 0.5142 | 0.8255 | 350 | 0.4989 | 0.2272 | 0.1646 | 0.0755 | 0.9063 | 0.9023 | 0.9036 |
| 0.4951 | 0.9434 | 400 | 0.4928 | 0.2152 | 0.1618 | 0.0713 | 0.9098 | 0.9062 | 0.9073 |
| 0.2467 | 1.0613 | 450 | 0.4990 | 0.2084 | 0.1510 | 0.0648 | 0.9155 | 0.9106 | 0.9126 |
| 0.211 | 1.1792 | 500 | 0.4999 | 0.2185 | 0.1579 | 0.0705 | 0.9097 | 0.9048 | 0.9068 |
### Framework versions
- Transformers 4.52.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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