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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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