---
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
  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

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: 1.0862

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.8893        | 0.6494  | 200  | 0.6173          |
| 0.4959        | 1.2987  | 400  | 0.5871          |
| 0.4654        | 1.9481  | 600  | 0.5799          |
| 0.308         | 2.5974  | 800  | 0.6095          |
| 0.2504        | 3.2468  | 1000 | 0.6823          |
| 0.1877        | 3.8961  | 1200 | 0.6828          |
| 0.1028        | 4.5455  | 1400 | 0.7804          |
| 0.0896        | 5.1948  | 1600 | 0.8240          |
| 0.0516        | 5.8442  | 1800 | 0.8491          |
| 0.0291        | 6.4935  | 2000 | 0.9035          |
| 0.0276        | 7.1429  | 2200 | 0.9402          |
| 0.0141        | 7.7922  | 2400 | 0.9443          |
| 0.0098        | 8.4416  | 2600 | 0.9972          |
| 0.0073        | 9.0909  | 2800 | 1.0118          |
| 0.0056        | 9.7403  | 3000 | 1.0176          |
| 0.0027        | 10.3896 | 3200 | 1.0468          |
| 0.0021        | 11.0390 | 3400 | 1.0564          |
| 0.0016        | 11.6883 | 3600 | 1.0703          |
| 0.0009        | 12.3377 | 3800 | 1.0840          |
| 0.0011        | 12.9870 | 4000 | 1.0862          |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1