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---
library_name: transformers
language:
- en
license: cc-by-sa-4.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- sage-bergerson/edacc_processed
model-index:
- name: Whisper Large EdAcc V3
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 EdAcc V3
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the EdAcc dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5752
## 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-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 600
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6164 | 1.9481 | 600 | 0.5752 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1 |