---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-base-small-yt-os
  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-v3-base-small-yt-os

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2389

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2985        | 0.03  | 300  | 0.3361          |
| 0.2869        | 0.06  | 600  | 0.3195          |
| 0.2795        | 0.09  | 900  | 0.3062          |
| 0.2779        | 0.12  | 1200 | 0.2890          |
| 0.2752        | 0.15  | 1500 | 0.2973          |
| 0.2818        | 0.18  | 1800 | 0.2881          |
| 0.2713        | 0.21  | 2100 | 0.2874          |
| 0.2693        | 0.24  | 2400 | 0.2807          |
| 0.2657        | 0.28  | 2700 | 0.2731          |
| 0.2652        | 0.31  | 3000 | 0.2726          |
| 0.2583        | 0.34  | 3300 | 0.2680          |
| 0.2607        | 0.37  | 3600 | 0.2767          |
| 0.2616        | 0.4   | 3900 | 0.2660          |
| 0.2566        | 0.43  | 4200 | 0.2684          |
| 0.2527        | 0.46  | 4500 | 0.2525          |
| 0.257         | 0.49  | 4800 | 0.2582          |
| 0.2558        | 0.52  | 5100 | 0.2641          |
| 0.2572        | 0.55  | 5400 | 0.2545          |
| 0.2485        | 0.58  | 5700 | 0.2620          |
| 0.2479        | 0.61  | 6000 | 0.2551          |
| 0.2494        | 0.64  | 6300 | 0.2490          |
| 0.2466        | 0.67  | 6600 | 0.2496          |
| 0.25          | 0.7   | 6900 | 0.2492          |
| 0.2513        | 0.73  | 7200 | 0.2509          |
| 0.246         | 0.76  | 7500 | 0.2515          |
| 0.2506        | 0.8   | 7800 | 0.2428          |
| 0.2483        | 0.83  | 8100 | 0.2367          |
| 0.2501        | 0.86  | 8400 | 0.2399          |
| 0.2464        | 0.89  | 8700 | 0.2491          |
| 0.2402        | 0.92  | 9000 | 0.2448          |
| 0.246         | 0.95  | 9300 | 0.2418          |
| 0.251         | 0.98  | 9600 | 0.2389          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2