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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-cv16-1__car200-e3n4-A50E100_owner12-copy2x-241217-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-large-v2-ft-cv16-1__car200-e3n4-A50E100_owner12-copy2x-241217-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: 0.1109
## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.7195 | 1.0 | 149 | 1.4206 |
| 0.3691 | 2.0 | 298 | 0.1129 |
| 0.1193 | 3.0 | 447 | 0.1035 |
| 0.0939 | 4.0 | 596 | 0.0994 |
| 0.0769 | 5.0 | 745 | 0.1003 |
| 0.0634 | 6.0 | 894 | 0.1031 |
| 0.053 | 7.0 | 1043 | 0.1054 |
| 0.0455 | 8.0 | 1192 | 0.1077 |
| 0.0402 | 9.0 | 1341 | 0.1098 |
| 0.0365 | 10.0 | 1490 | 0.1109 |
### Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0 |