---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: whisper-base.en-fsc
  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-base.en-fsc

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0278
- Accuracy: 0.5630

## 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: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9972  | 263  | 3.7447          | 0.0962   |
| No log        | 1.9981  | 527  | 2.8087          | 0.3060   |
| No log        | 2.9991  | 791  | 2.3083          | 0.4062   |
| 2.9232        | 4.0     | 1055 | 2.0094          | 0.4940   |
| 2.9232        | 4.9972  | 1318 | 1.9099          | 0.5321   |
| 2.9232        | 5.9981  | 1582 | 1.9257          | 0.5479   |
| 2.9232        | 6.9991  | 1846 | 2.0132          | 0.5479   |
| 0.8199        | 8.0     | 2110 | 2.1486          | 0.5444   |
| 0.8199        | 8.9972  | 2373 | 2.2976          | 0.5440   |
| 0.8199        | 9.9981  | 2637 | 2.4131          | 0.5453   |
| 0.8199        | 10.9991 | 2901 | 2.5031          | 0.5523   |
| 0.1503        | 12.0    | 3165 | 2.6273          | 0.5544   |
| 0.1503        | 12.9972 | 3428 | 2.7233          | 0.5581   |
| 0.1503        | 13.9981 | 3692 | 2.8470          | 0.5498   |
| 0.1503        | 14.9991 | 3956 | 2.8848          | 0.5589   |
| 0.0246        | 16.0    | 4220 | 2.9497          | 0.5605   |
| 0.0246        | 16.9972 | 4483 | 2.9992          | 0.5612   |
| 0.0246        | 17.9981 | 4747 | 3.0278          | 0.5630   |
| 0.0043        | 18.9991 | 5011 | 3.0502          | 0.5629   |
| 0.0043        | 19.9431 | 5260 | 3.0561          | 0.5629   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1