---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_lv2_v1
  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_lv2_v1

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2485
- Wer: 18.7231

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1687        | 1.0   | 48   | 1.0313          | 19.8231 |
| 0.042         | 2.0   | 96   | 1.0421          | 18.3166 |
| 0.0189        | 3.0   | 144  | 1.0886          | 18.4840 |
| 0.0125        | 4.0   | 192  | 1.1275          | 18.0057 |
| 0.0108        | 5.0   | 240  | 1.1485          | 17.7905 |
| 0.0106        | 6.0   | 288  | 1.1270          | 17.1927 |
| 0.0072        | 7.0   | 336  | 1.1054          | 16.0928 |
| 0.0076        | 8.0   | 384  | 1.1554          | 17.6471 |
| 0.0083        | 9.0   | 432  | 1.2121          | 18.1731 |
| 0.0093        | 10.0  | 480  | 1.2485          | 18.7231 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0