---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: my-seq2seq-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
    metrics:
    - name: Wer
      type: wer
      value: 0.35424354243542433
---

<!-- 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. -->

# my-seq2seq-model

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7355
- Wer Ortho: 0.3526
- Wer: 0.3542

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| No log        | 1.0   | 57   | 0.5982          | 0.3546    | 0.3536 |
| No log        | 2.0   | 114  | 0.6244          | 0.3816    | 0.3838 |
| No log        | 3.0   | 171  | 0.6240          | 0.3662    | 0.3629 |
| No log        | 4.0   | 228  | 0.6321          | 0.3423    | 0.3426 |
| No log        | 5.0   | 285  | 0.6522          | 0.3732    | 0.3715 |
| No log        | 6.0   | 342  | 0.6582          | 0.3526    | 0.3524 |
| No log        | 7.0   | 399  | 0.6628          | 0.3507    | 0.3506 |
| No log        | 8.0   | 456  | 0.6683          | 0.3501    | 0.3499 |
| 0.0203        | 9.0   | 513  | 0.6734          | 0.3443    | 0.3444 |
| 0.0203        | 10.0  | 570  | 0.6804          | 0.3456    | 0.3456 |
| 0.0203        | 11.0  | 627  | 0.6837          | 0.3430    | 0.3432 |
| 0.0203        | 12.0  | 684  | 0.6878          | 0.3468    | 0.3456 |
| 0.0203        | 13.0  | 741  | 0.6939          | 0.3481    | 0.3469 |
| 0.0203        | 14.0  | 798  | 0.6960          | 0.3501    | 0.3487 |
| 0.0203        | 15.0  | 855  | 0.6991          | 0.3481    | 0.3469 |
| 0.0203        | 16.0  | 912  | 0.7017          | 0.3468    | 0.3475 |
| 0.0203        | 17.0  | 969  | 0.7044          | 0.3468    | 0.3475 |
| 0.0024        | 18.0  | 1026 | 0.7082          | 0.3507    | 0.3506 |
| 0.0024        | 19.0  | 1083 | 0.7089          | 0.3507    | 0.3506 |
| 0.0024        | 20.0  | 1140 | 0.7131          | 0.3533    | 0.3536 |
| 0.0024        | 21.0  | 1197 | 0.7141          | 0.3546    | 0.3549 |
| 0.0024        | 22.0  | 1254 | 0.7176          | 0.3520    | 0.3518 |
| 0.0024        | 23.0  | 1311 | 0.7197          | 0.3507    | 0.3506 |
| 0.0024        | 24.0  | 1368 | 0.7211          | 0.3507    | 0.3506 |
| 0.0024        | 25.0  | 1425 | 0.7223          | 0.3501    | 0.3499 |
| 0.0024        | 26.0  | 1482 | 0.7243          | 0.3501    | 0.3499 |
| 0.0014        | 27.0  | 1539 | 0.7255          | 0.3507    | 0.3506 |
| 0.0014        | 28.0  | 1596 | 0.7264          | 0.3514    | 0.3512 |
| 0.0014        | 29.0  | 1653 | 0.7293          | 0.3520    | 0.3524 |
| 0.0014        | 30.0  | 1710 | 0.7297          | 0.3514    | 0.3518 |
| 0.0014        | 31.0  | 1767 | 0.7310          | 0.3507    | 0.3518 |
| 0.0014        | 32.0  | 1824 | 0.7308          | 0.3507    | 0.3518 |
| 0.0014        | 33.0  | 1881 | 0.7330          | 0.3507    | 0.3518 |
| 0.0014        | 34.0  | 1938 | 0.7336          | 0.3507    | 0.3518 |
| 0.0014        | 35.0  | 1995 | 0.7338          | 0.3507    | 0.3518 |
| 0.0010        | 36.0  | 2052 | 0.7341          | 0.3526    | 0.3542 |
| 0.0010        | 37.0  | 2109 | 0.7349          | 0.3520    | 0.3530 |
| 0.0010        | 38.0  | 2166 | 0.7350          | 0.3526    | 0.3542 |
| 0.0010        | 39.0  | 2223 | 0.7356          | 0.3520    | 0.3530 |
| 0.0010        | 40.0  | 2280 | 0.7355          | 0.3526    | 0.3542 |


### Framework versions

- Transformers 5.14.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2