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Model: GwadaDLT/whisper-base-gcf
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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-gcf
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-gcf
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4385
- Wer: 100.1274
## 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: 100
- training_steps: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 0.9963 | 1.4085 | 200 | 3.4896 | 101.2739 |
| 0.6015 | 2.8169 | 400 | 3.0877 | 1097.9618 |
| 0.3216 | 4.2254 | 600 | 2.8618 | 99.7452 |
| 0.2368 | 5.6338 | 800 | 2.6891 | 100.1274 |
| 0.1739 | 7.0423 | 1000 | 2.5483 | 421.6561 |
| 0.1892 | 8.4507 | 1200 | 2.4829 | 104.5860 |
| 0.1273 | 9.8592 | 1400 | 2.4358 | 1683.6943 |
| 0.1256 | 10.5634 | 1500 | 2.4385 | 100.1274 |
### Framework versions
- Transformers 5.5.0
- Pytorch 2.4.1+cu124
- Datasets 3.6.0
- Tokenizers 0.22.2

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