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---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-finetuned2222222222222222222222222222222
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-finetuned2222222222222222222222222222222
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0018
- Wer: 0.125
## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 400
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.7056 | 0.8 | 20 | 6.4502 | 16.25 |
| 4.7836 | 1.6 | 40 | 2.9149 | 10.375 |
| 1.8399 | 2.4 | 60 | 0.8254 | 7.875 |
| 0.3132 | 3.2 | 80 | 0.0852 | 3.875 |
| 0.0335 | 4.0 | 100 | 0.0190 | 1.7500 |
| 0.0067 | 4.8 | 120 | 0.0080 | 1.0 |
| 0.0032 | 5.6 | 140 | 0.0050 | 0.375 |
| 0.0021 | 6.4 | 160 | 0.0039 | 0.125 |
| 0.0017 | 7.2 | 180 | 0.0034 | 0.125 |
| 0.0015 | 8.0 | 200 | 0.0030 | 0.125 |
| 0.0013 | 8.8 | 220 | 0.0027 | 0.125 |
| 0.0012 | 9.6 | 240 | 0.0025 | 0.125 |
| 0.0011 | 10.4 | 260 | 0.0023 | 0.125 |
| 0.001 | 11.2 | 280 | 0.0021 | 0.125 |
| 0.0009 | 12.0 | 300 | 0.0020 | 0.125 |
| 0.0009 | 12.8 | 320 | 0.0020 | 0.125 |
| 0.0009 | 13.6 | 340 | 0.0019 | 0.125 |
| 0.0008 | 14.4 | 360 | 0.0018 | 0.125 |
| 0.0009 | 15.2 | 380 | 0.0018 | 0.125 |
| 0.0008 | 16.0 | 400 | 0.0018 | 0.125 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.2
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