---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-medium
datasets:
- generator
metrics:
- wer
model-index:
- name: whisper-medium-ach
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - type: wer
      value: 62.298387096774185
      name: Wer
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bakera-sunbird/huggingface/runs/pkvclqhs)
# whisper-medium-ach

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3501
- Wer: 62.2984

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.081         | 0.05    | 200  | 0.4844          | 138.8609 |
| 0.592         | 1.0248  | 400  | 0.3859          | 154.4355 |
| 0.5445        | 1.0748  | 600  | 0.3434          | 146.1694 |
| 0.3446        | 2.0495  | 800  | 0.3272          | 163.9113 |
| 0.2614        | 3.0242  | 1000 | 0.3098          | 86.2903  |
| 0.2542        | 3.0743  | 1200 | 0.3414          | 91.4315  |
| 0.1972        | 4.049   | 1400 | 0.3289          | 89.3145  |
| 0.1172        | 5.0237  | 1600 | 0.3224          | 100.1008 |
| 0.1226        | 5.0738  | 1800 | 0.3377          | 72.3286  |
| 0.0721        | 6.0485  | 2000 | 0.3277          | 105.8972 |
| 0.0504        | 7.0232  | 2200 | 0.3483          | 80.1411  |
| 0.0503        | 7.0732  | 2400 | 0.3514          | 95.0101  |
| 0.0375        | 8.048   | 2600 | 0.3378          | 64.5665  |
| 0.0348        | 9.0228  | 2800 | 0.3492          | 122.5806 |
| 0.0338        | 9.0727  | 3000 | 0.3502          | 88.6089  |
| 0.0273        | 10.0475 | 3200 | 0.3554          | 88.2560  |
| 0.0194        | 11.0222 | 3400 | 0.3501          | 62.2984  |
| 0.0165        | 11.0723 | 3600 | 0.3478          | 73.3871  |
| 0.0117        | 12.047  | 3800 | 0.3618          | 74.2440  |
| 0.0125        | 13.0218 | 4000 | 0.3587          | 97.6815  |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.0
- Datasets 2.19.1.dev0
- Tokenizers 0.19.1