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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
base_model: openai/whisper-large-v2
model-index:
- name: openai-whisper-large-v2-LORA-colab
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. -->
# openai-whisper-large-v2-LORA-colab
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1374
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1865 | 1.0 | 1410 | 0.1704 |
| 0.0955 | 2.0 | 2820 | 0.1426 |
| 0.0165 | 3.0 | 4230 | 0.1374 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1.dev0
- Tokenizers 0.15.1 |