metadata
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
hamsa-tiny-finetuned-qasr
This model is a fine-tuned version of 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