transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer en dataset:team4/8dretnaEN base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- team4/8dretnaEN
metrics:
- wer
model-index:
- name: whisperEN
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: 8dretnaEN
      type: team4/8dretnaEN
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 29.831932773109244
---

<!-- 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. -->

# whisperEN

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the 8dretnaEN dataset.
It achieves the following results on the evaluation set:
- Loss: 5.8051
- Wer: 29.8319

## 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: 10
- 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: 5
- training_steps: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 5.5291        | 0.03  | 5    | 5.8051          | 29.8319 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
