---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-cit-synth-do0.15-wd0-lr1e-06-1000
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-large-cit-synth-do0.15-wd0-lr1e-06-1000

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3877
- Wer: 24.9123

## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.0947        | 0.3556 | 20   | 0.8311          | 36.7251 |
| 0.8896        | 0.7111 | 40   | 0.7202          | 34.7368 |
| 0.8418        | 1.0667 | 60   | 0.6216          | 32.0078 |
| 0.6567        | 1.4222 | 80   | 0.5254          | 30.7212 |
| 0.5491        | 1.7778 | 100  | 0.4690          | 27.6803 |
| 0.5497        | 2.1333 | 120  | 0.4368          | 26.6667 |
| 0.4875        | 2.4889 | 140  | 0.4211          | 25.7310 |
| 0.4721        | 2.8444 | 160  | 0.4124          | 25.3801 |
| 0.46          | 3.2    | 180  | 0.4026          | 25.3801 |
| 0.4342        | 3.5556 | 200  | 0.3960          | 24.9513 |
| 0.4248        | 3.9111 | 220  | 0.3945          | 24.8733 |
| 0.4249        | 4.2667 | 240  | 0.3916          | 24.9123 |
| 0.4192        | 4.6222 | 260  | 0.3899          | 24.7953 |
| 0.3823        | 4.9778 | 280  | 0.3884          | 24.6004 |
| 0.4176        | 5.3333 | 300  | 0.3877          | 24.9123 |


### Framework versions

- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1