---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_large_v2_newdata
  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_newdata

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6261
- Cer: 14.4482
- Wer: 24.5386

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Cer     | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
| 0.9203        | 0.9999 | 5765  | 0.6477          | 16.6649 | 28.2685 |
| 0.6189        | 1.9998 | 11530 | 0.6261          | 14.4482 | 24.5386 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1