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---
base_model: openai/whisper-large-v2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-ft-my_dataset_snr0_owner12_MPSENet-241018_bs8
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-ft-my_dataset_snr0_owner12_MPSENet-241018_bs8
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: 0.0049
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.8653 | 1.6667 | 25 | 0.8638 |
| 0.1675 | 3.3333 | 50 | 0.0171 |
| 0.0101 | 5.0 | 75 | 0.0068 |
| 0.0025 | 6.6667 | 100 | 0.0032 |
| 0.0 | 8.3333 | 125 | 0.0091 |
| 0.0 | 10.0 | 150 | 0.0049 |
### Framework versions
- PEFT 0.13.0
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1 |