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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
- precision
- recall
- f1
model-index:
- name: ./whisper-base-ea_base_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-base-ea_base_v2
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Afrispeech-200 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0084
- Wer Ortho: 0.3014
- Wer: 0.2499
- Cer: 0.1058
- Precision: 0.8391
- Recall: 0.8445
- F1: 0.8412
## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | Cer | Precision | Recall | F1 |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|:------:|:------:|
| 0.1669 | 2.1186 | 500 | 0.7136 | 0.2789 | 0.2257 | 0.1014 | 0.8596 | 0.8608 | 0.8593 |
| 0.0787 | 4.2373 | 1000 | 0.7690 | 0.2915 | 0.2394 | 0.1081 | 0.8514 | 0.8536 | 0.8515 |
| 0.0243 | 6.3559 | 1500 | 0.8373 | 0.2916 | 0.2405 | 0.1010 | 0.8461 | 0.8531 | 0.8491 |
| 0.012 | 8.4746 | 2000 | 0.8798 | 0.2880 | 0.2372 | 0.1005 | 0.8484 | 0.8551 | 0.8512 |
| 0.0081 | 10.5932 | 2500 | 0.9189 | 0.2966 | 0.2459 | 0.1047 | 0.8422 | 0.8477 | 0.8443 |
| 0.0038 | 12.7119 | 3000 | 0.9609 | 0.2955 | 0.2460 | 0.1025 | 0.8428 | 0.8493 | 0.8455 |
| 0.0048 | 14.8305 | 3500 | 0.9747 | 0.2971 | 0.2483 | 0.1051 | 0.8423 | 0.8478 | 0.8445 |
| 0.0039 | 16.9492 | 4000 | 1.0084 | 0.3014 | 0.2499 | 0.1058 | 0.8391 | 0.8445 | 0.8412 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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