File size: 2,183 Bytes
114f96e |
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 |
---
language:
- tr
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: base Turkish Whisper (bTW)
results: []
---
<!-- 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. -->
# base Turkish Whisper (bTW)
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Ermetal Meetings dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5006
- Wer: 1.3698
- Cer: 1.1255
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.8141 | 5.53 | 100 | 1.4784 | 0.7680 | 0.4463 |
| 0.673 | 11.11 | 200 | 1.0561 | 0.8175 | 0.5889 |
| 0.2762 | 16.64 | 300 | 1.0746 | 0.8564 | 0.5887 |
| 0.0852 | 22.21 | 400 | 1.2061 | 1.4290 | 0.9567 |
| 0.0199 | 27.75 | 500 | 1.2649 | 1.0706 | 0.9168 |
| 0.0087 | 33.32 | 600 | 1.4641 | 1.2417 | 1.0328 |
| 0.0041 | 38.85 | 700 | 1.4685 | 1.2806 | 0.9546 |
| 0.003 | 44.43 | 800 | 1.4830 | 1.3633 | 1.0236 |
| 0.0026 | 49.96 | 900 | 1.4964 | 1.3698 | 1.0375 |
| 0.0025 | 55.53 | 1000 | 1.5006 | 1.3698 | 1.1255 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
|