File size: 2,183 Bytes
f50c5b3 |
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: 1.1451
- Wer: 1.0165
- Cer: 0.7894
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.6901 | 4.54 | 100 | 1.3928 | 0.8093 | 0.4264 |
| 0.6163 | 9.09 | 200 | 0.8885 | 0.7907 | 0.4532 |
| 0.2692 | 13.63 | 300 | 0.8719 | 0.7823 | 0.4474 |
| 0.1148 | 18.18 | 400 | 0.9275 | 0.7393 | 0.4280 |
| 0.04 | 22.72 | 500 | 1.0308 | 0.8162 | 0.5241 |
| 0.0114 | 27.27 | 600 | 1.0885 | 0.9666 | 0.7902 |
| 0.0051 | 31.81 | 700 | 1.1159 | 0.9594 | 0.6967 |
| 0.0036 | 36.36 | 800 | 1.1301 | 1.0451 | 0.7819 |
| 0.0031 | 40.9 | 900 | 1.1415 | 1.0496 | 0.8072 |
| 0.0028 | 45.45 | 1000 | 1.1451 | 1.0165 | 0.7894 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
|