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---

license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny.en-finetuned
  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-tiny.en-finetuned

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4890
- Wer: 0.8750
- Cer: 0.4454
- Ser: 0.055

## 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: 64

- seed: 42

- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08

- lr_scheduler_type: linear

- lr_scheduler_warmup_steps: 20
- training_steps: 220

- mixed_precision_training: Native AMP



### Training results



| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer     | Ser   |

|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-----:|

| 6.4419        | 0.4   | 10   | 6.4480          | 45.25  | 16.3573 | 1.0   |

| 6.2706        | 0.8   | 20   | 5.9268          | 39.375 | 14.1797 | 1.0   |

| 5.3444        | 1.2   | 30   | 4.8418          | 19.875 | 7.3002  | 1.0   |

| 4.3269        | 1.6   | 40   | 3.9103          | 9.375  | 3.8357  | 1.0   |

| 3.6103        | 2.0   | 50   | 3.3228          | 7.0000 | 3.2170  | 1.0   |

| 3.0331        | 2.4   | 60   | 2.7725          | 5.375  | 2.3509  | 1.0   |

| 2.5529        | 2.8   | 70   | 2.3913          | 4.75   | 1.8312  | 1.0   |

| 2.2359        | 3.2   | 80   | 2.1217          | 3.375  | 1.4353  | 1.0   |

| 1.9777        | 3.6   | 90   | 1.8790          | 3.0    | 1.3116  | 1.0   |

| 1.7863        | 4.0   | 100  | 1.7402          | 2.875  | 1.0393  | 0.98  |

| 1.6854        | 4.4   | 110  | 1.6736          | 2.625  | 0.9651  | 0.925 |

| 1.6297        | 4.8   | 120  | 1.6290          | 2.625  | 0.9404  | 0.765 |

| 1.5974        | 5.2   | 130  | 1.5959          | 2.5    | 0.9651  | 0.57  |

| 1.5673        | 5.6   | 140  | 1.5702          | 1.5    | 0.6434  | 0.385 |

| 1.5397        | 6.0   | 150  | 1.5497          | 1.25   | 0.5692  | 0.27  |

| 1.524         | 6.4   | 160  | 1.5333          | 1.125  | 0.5444  | 0.22  |

| 1.509         | 6.8   | 170  | 1.5199          | 0.8750 | 0.4454  | 0.155 |

| 1.4986        | 7.2   | 180  | 1.5091          | 0.8750 | 0.4454  | 0.095 |

| 1.4872        | 7.6   | 190  | 1.5011          | 0.8750 | 0.4454  | 0.075 |

| 1.4844        | 8.0   | 200  | 1.4950          | 0.8750 | 0.4454  | 0.075 |

| 1.4743        | 8.4   | 210  | 1.4910          | 0.8750 | 0.4454  | 0.065 |

| 1.4746        | 8.8   | 220  | 1.4890          | 0.8750 | 0.4454  | 0.055 |





### Framework versions



- Transformers 4.39.3

- Pytorch 2.2.2+cu121

- Datasets 2.14.5

- Tokenizers 0.15.2