transformers tensorboard safetensors whisper automatic-speech-recognition FS_voice_calls generated_from_trainer ru dataset:FSphone-calls-whisper-LARGE base_model:openai/whisper-large-v2 license:apache-2.0 endpoints_compatible region:us
---
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
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# 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
