transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:nadsoft/QASR-Speech-Resource base_model:nadsoft/Hamsa-tiny model-index endpoints_compatible region:us
---
base_model: nadsoft/Hamsa-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- nadsoft/QASR-Speech-Resource
metrics:
- wer
model-index:
- name: hamsa-tiny-pretrained
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nadsoft/QASR-Speech-Resource default
      type: nadsoft/QASR-Speech-Resource
    metrics:
    - name: Wer
      type: wer
      value: 28.726358005647974
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hamsa-tiny-pretrained

This model is a fine-tuned version of [nadsoft/Hamsa-tiny](https://huggingface.co/nadsoft/Hamsa-tiny) on the nadsoft/QASR-Speech-Resource default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3795
- Wer: 28.7264

## 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: 64
- 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: 50000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.6597        | 0.1   | 2500  | 0.6394          | 48.8384 |
| 0.5442        | 0.2   | 5000  | 0.5455          | 41.8543 |
| 0.4954        | 0.3   | 7500  | 0.5018          | 39.8609 |
| 0.474         | 0.4   | 10000 | 0.4770          | 38.5534 |
| 0.4696        | 0.5   | 12500 | 0.4566          | 36.2515 |
| 0.4312        | 0.6   | 15000 | 0.4433          | 36.8780 |
| 0.4208        | 0.7   | 17500 | 0.4308          | 32.3714 |
| 0.4089        | 0.8   | 20000 | 0.4229          | 33.4109 |
| 0.4163        | 0.9   | 22500 | 0.4143          | 32.5423 |
| 0.3831        | 1.0   | 25000 | 0.4077          | 31.6951 |
| 0.3842        | 1.1   | 27500 | 0.4023          | 33.6316 |
| 0.3848        | 1.2   | 30000 | 0.3984          | 30.1099 |
| 0.3774        | 1.3   | 32500 | 0.3948          | 29.2864 |
| 0.3667        | 1.4   | 35000 | 0.3912          | 29.5166 |
| 0.3674        | 1.5   | 37500 | 0.3881          | 29.6115 |
| 0.3721        | 1.6   | 40000 | 0.3851          | 30.4065 |
| 0.3533        | 1.7   | 42500 | 0.3834          | 27.9693 |
| 0.3594        | 1.8   | 45000 | 0.3815          | 28.8569 |
| 0.3628        | 1.9   | 47500 | 0.3802          | 28.1260 |
| 0.3392        | 2.0   | 50000 | 0.3795          | 28.7264 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
