---
base_model: nadsoft/hamsa_small
tags:
- whisper-event
- generated_from_trainer
datasets:
- nadsoft/QASR-Speech-Resource
metrics:
- wer
model-index:
- name: hamsa-small-finetuned-qasr
  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: 22.587152044424403
---

<!-- 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. -->

# hamsa-small-finetuned-qasr

This model is a fine-tuned version of [nadsoft/hamsa_small](https://huggingface.co/nadsoft/hamsa_small) on the nadsoft/QASR-Speech-Resource default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2831
- Wer: 22.5872

## 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: 16
- 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: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3207        | 0.03  | 2500  | 0.3458          | 24.4928 |
| 0.3264        | 0.05  | 5000  | 0.3316          | 23.4082 |
| 0.3223        | 0.08  | 7500  | 0.3239          | 25.1050 |
| 0.3121        | 0.1   | 10000 | 0.3143          | 23.4557 |
| 0.3103        | 0.13  | 12500 | 0.3079          | 23.4296 |
| 0.3041        | 0.15  | 15000 | 0.3033          | 23.2113 |
| 0.3077        | 0.18  | 17500 | 0.2998          | 21.7091 |
| 0.2867        | 0.2   | 20000 | 0.2943          | 20.1761 |
| 0.265         | 0.23  | 22500 | 0.2921          | 21.6522 |
| 0.3096        | 0.25  | 25000 | 0.2894          | 22.1505 |
| 0.2813        | 0.28  | 27500 | 0.2863          | 22.4993 |
| 0.2805        | 0.3   | 30000 | 0.2832          | 21.0114 |


### Framework versions

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