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---
base_model: openai/whisper-large-v2
datasets:
- common_voice_16_1
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-finetuned
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/keviinkibe/huggingface/runs/l6qwxkcg)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/keviinkibe/huggingface/runs/l6qwxkcg)
# whisper-large-v2-finetuned
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.3976
- eval_wer: 102.8686
- eval_runtime: 329.5091
- eval_samples_per_second: 0.492
- eval_steps_per_second: 0.012
- epoch: 125.0
- step: 1000
## 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: 0.0001
- train_batch_size: 50
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 10
- training_steps: 1000
- mixed_precision_training: Native AMP
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1