transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:nadsoft/QASR-Speech-Resource base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- nadsoft/QASR-Speech-Resource
metrics:
- wer
model-index:
- name: hamsa-tiny-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: 25.45148200004746
---

<!-- 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-finetuned-qasr

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the nadsoft/QASR-Speech-Resource default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3310
- Wer: 25.4515

## 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: 150000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Wer     |
|:-------------:|:-----:|:------:|:---------------:|:-------:|
| 0.643         | 0.1   | 2500   | 0.6272          | 51.4156 |
| 0.5445        | 0.2   | 5000   | 0.5443          | 40.7508 |
| 0.4944        | 0.3   | 7500   | 0.5005          | 38.5676 |
| 0.4722        | 0.4   | 10000  | 0.4747          | 39.1490 |
| 0.4659        | 0.5   | 12500  | 0.4541          | 35.6867 |
| 0.4261        | 0.6   | 15000  | 0.4383          | 36.0877 |
| 0.4166        | 0.7   | 17500  | 0.4257          | 31.8968 |
| 0.4051        | 0.8   | 20000  | 0.4160          | 32.5898 |
| 0.4107        | 0.9   | 22500  | 0.4070          | 32.9291 |
| 0.3753        | 1.0   | 25000  | 0.3996          | 30.2095 |
| 0.3755        | 1.1   | 27500  | 0.3943          | 32.4497 |
| 0.3749        | 1.2   | 30000  | 0.3893          | 31.3320 |
| 0.3697        | 1.3   | 32500  | 0.3856          | 30.2024 |
| 0.3574        | 1.4   | 35000  | 0.3802          | 27.4662 |
| 0.3583        | 1.5   | 37500  | 0.3774          | 28.9257 |
| 0.3619        | 1.6   | 40000  | 0.3731          | 28.9447 |
| 0.3414        | 1.7   | 42500  | 0.3702          | 27.6751 |
| 0.3465        | 1.8   | 45000  | 0.3667          | 27.2716 |
| 0.3489        | 1.9   | 47500  | 0.3640          | 25.7695 |
| 0.3173        | 2.0   | 50000  | 0.3623          | 26.2773 |
| 0.3227        | 2.11  | 52500  | 0.3608          | 25.5844 |
| 0.3236        | 2.21  | 55000  | 0.3592          | 26.8564 |
| 0.324         | 2.31  | 57500  | 0.3565          | 27.4639 |
| 0.3315        | 2.41  | 60000  | 0.3555          | 26.7187 |
| 0.3238        | 2.51  | 62500  | 0.3531          | 26.3343 |
| 0.3406        | 2.61  | 65000  | 0.3513          | 26.4031 |
| 0.3214        | 2.71  | 67500  | 0.3496          | 25.1999 |
| 0.3197        | 2.81  | 70000  | 0.3481          | 25.4657 |
| 0.3232        | 2.91  | 72500  | 0.3463          | 24.6684 |
| 0.3136        | 3.01  | 75000  | 0.3456          | 25.8668 |
| 0.3082        | 3.11  | 77500  | 0.3445          | 26.3248 |
| 0.3058        | 3.21  | 80000  | 0.3439          | 25.3874 |
| 0.3217        | 3.31  | 82500  | 0.3434          | 25.1857 |
| 0.3158        | 3.41  | 85000  | 0.3417          | 24.5521 |
| 0.3021        | 3.51  | 87500  | 0.3414          | 25.6295 |
| 0.2912        | 3.61  | 90000  | 0.3405          | 24.7941 |
| 0.281         | 3.71  | 92500  | 0.3402          | 24.5426 |
| 0.3017        | 3.81  | 95000  | 0.3391          | 25.1809 |
| 0.2986        | 3.91  | 97500  | 0.3387          | 25.1145 |
| 0.2996        | 4.01  | 100000 | 0.3377          | 24.6185 |
| 0.2734        | 4.11  | 102500 | 0.3374          | 24.7229 |
| 0.3088        | 4.21  | 105000 | 0.3373          | 24.2578 |
| 0.2794        | 4.31  | 107500 | 0.3361          | 25.6532 |
| 0.2988        | 4.41  | 110000 | 0.3357          | 25.7813 |
| 0.3085        | 4.51  | 112500 | 0.3352          | 24.8345 |
| 0.2888        | 4.61  | 115000 | 0.3346          | 24.5687 |
| 0.2923        | 4.71  | 117500 | 0.3342          | 25.0006 |
| 0.2782        | 4.81  | 120000 | 0.3336          | 25.7766 |
| 0.2948        | 4.91  | 122500 | 0.3334          | 25.2355 |
| 0.2791        | 5.01  | 125000 | 0.3329          | 25.6057 |
| 0.2988        | 5.11  | 127500 | 0.3333          | 25.6129 |
| 0.2933        | 5.21  | 130000 | 0.3330          | 25.7291 |
| 0.2801        | 5.31  | 132500 | 0.3321          | 25.7529 |
| 0.2885        | 5.41  | 135000 | 0.3325          | 25.7861 |
| 0.2953        | 5.51  | 137500 | 0.3319          | 25.0742 |
| 0.2677        | 5.61  | 140000 | 0.3319          | 25.2379 |
| 0.2833        | 5.71  | 142500 | 0.3315          | 25.5749 |
| 0.2923        | 5.81  | 145000 | 0.3313          | 25.6627 |
| 0.2602        | 5.91  | 147500 | 0.3311          | 25.4467 |
| 0.2757        | 6.01  | 150000 | 0.3310          | 25.4515 |


### Framework versions

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