File size: 2,640 Bytes
63f94f6 b557216 63f94f6 b557216 63f94f6 b557216 63f94f6 b557216 63f94f6 b557216 63f94f6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 |
---
library_name: peft
language:
- tr
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- asr
- whisper
- lora
- Turkish
- tr
- generated_from_trainer
datasets:
- dcl-ai-team/CommonVoice-17_tr_bandpass_filter_telephonic
metrics:
- wer
model-index:
- name: v3-turbo-cv17-telephonic-lora
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: CommonVoice-17_tr_bandpass_filter_telephonic
type: dcl-ai-team/CommonVoice-17_tr_bandpass_filter_telephonic
metrics:
- type: wer
value: 14.208987174831321
name: Wer
---
<!-- 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. -->
# v3-turbo-cv17-telephonic-lora
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the CommonVoice-17_tr_bandpass_filter_telephonic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1411
- Wer: 14.2090
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.454 | 0.1138 | 500 | 0.1633 | 15.3845 |
| 0.1463 | 0.2276 | 1000 | 0.1525 | 14.9965 |
| 0.1393 | 0.3414 | 1500 | 0.1482 | 14.7002 |
| 0.1344 | 0.4552 | 2000 | 0.1466 | 14.4383 |
| 0.1305 | 0.5690 | 2500 | 0.1442 | 14.3084 |
| 0.1235 | 0.6828 | 3000 | 0.1427 | 14.2510 |
| 0.129 | 0.7966 | 3500 | 0.1418 | 14.2434 |
| 0.1259 | 0.9104 | 4000 | 0.1416 | 14.1765 |
| 0.1169 | 1.0241 | 4500 | 0.1412 | 14.2185 |
| 0.1103 | 1.1379 | 5000 | 0.1411 | 14.2090 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0 |