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---
language:
- ru
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- FS_voice_calls
- generated_from_trainer
datasets:
- FSphone-calls-whisper-LARGE
metrics:
- wer
model-index:
- name: whisper-large-v2
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. -->
# whisper-large-v2
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the FS_phone_calls dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0867
- Wer: 98.9696
## 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: 5
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8251 | 3.33 | 100 | 1.7838 | 93.7146 |
| 1.0083 | 6.67 | 200 | 2.0824 | 92.7872 |
| 0.4413 | 10.0 | 300 | 2.2075 | 98.6090 |
| 0.131 | 13.33 | 400 | 2.5746 | 103.8125 |
| 0.0484 | 16.67 | 500 | 2.6733 | 107.2128 |
| 0.031 | 20.0 | 600 | 2.6507 | 99.4333 |
| 0.022 | 23.33 | 700 | 2.6682 | 103.2457 |
| 0.013 | 26.67 | 800 | 2.7772 | 105.3581 |
| 0.0135 | 30.0 | 900 | 2.7849 | 100.3091 |
| 0.0097 | 33.33 | 1000 | 2.7935 | 96.0845 |
| 0.005 | 36.67 | 1100 | 2.9164 | 94.8480 |
| 0.0039 | 40.0 | 1200 | 2.8849 | 100.8758 |
| 0.0031 | 43.33 | 1300 | 2.9600 | 100.4637 |
| 0.0013 | 46.67 | 1400 | 2.9947 | 104.1731 |
| 0.001 | 50.0 | 1500 | 3.0367 | 100.1030 |
| 0.001 | 53.33 | 1600 | 3.0172 | 95.2602 |
| 0.0008 | 56.67 | 1700 | 3.0539 | 100.2061 |
| 0.0007 | 60.0 | 1800 | 3.0730 | 100.4122 |
| 0.0006 | 63.33 | 1900 | 3.0813 | 99.1757 |
| 0.0006 | 66.67 | 2000 | 3.0867 | 98.9696 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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