tensorboard safetensors generated_from_trainer base_model:openai/whisper-large-v2 license:apache-2.0 region:us
---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-lora-cgn
  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-lora-cgn

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: 0.2623

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3312        | 0.17  | 50   | 0.3258          |
| 0.3107        | 0.35  | 100  | 0.3097          |
| 0.2899        | 0.52  | 150  | 0.2879          |
| 0.2851        | 0.69  | 200  | 0.2725          |
| 0.2856        | 0.86  | 250  | 0.2623          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
