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---
language:
- en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base EN
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 EN
This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the ADLINK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Wer: 1.2422
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.4205 | 33.33 | 100 | 1.0960 | 9.9379 |
| 0.4057 | 66.67 | 200 | 0.3715 | 1.5528 |
| 0.0908 | 100.0 | 300 | 0.0704 | 1.5528 |
| 0.0053 | 133.33 | 400 | 0.0037 | 1.5528 |
| 0.0011 | 166.67 | 500 | 0.0010 | 1.2422 |
| 0.0006 | 200.0 | 600 | 0.0006 | 1.2422 |
| 0.0004 | 233.33 | 700 | 0.0004 | 1.2422 |
| 0.0003 | 266.67 | 800 | 0.0003 | 1.2422 |
| 0.0003 | 300.0 | 900 | 0.0003 | 1.2422 |
| 0.0003 | 333.33 | 1000 | 0.0003 | 1.2422 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|