---
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: 0.0437
- Accuracy: 0.9950

## 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: 0.0005
- 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: 25

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9959  | 120  | 0.0862          | 0.9739   |
| No log        | 2.0     | 241  | 0.0422          | 0.9866   |
| No log        | 2.9959  | 361  | 0.0630          | 0.9823   |
| No log        | 4.0     | 482  | 0.0630          | 0.9805   |
| No log        | 4.9959  | 602  | 0.0626          | 0.9821   |
| No log        | 6.0     | 723  | 0.0339          | 0.9905   |
| No log        | 6.9959  | 843  | 0.0452          | 0.9897   |
| No log        | 8.0     | 964  | 0.0527          | 0.9834   |
| 0.1514        | 8.9959  | 1084 | 0.0637          | 0.9868   |
| 0.1514        | 10.0    | 1205 | 0.0443          | 0.9921   |
| 0.1514        | 10.9959 | 1325 | 0.0306          | 0.9937   |
| 0.1514        | 12.0    | 1446 | 0.0416          | 0.9897   |
| 0.1514        | 12.9959 | 1566 | 0.0363          | 0.9910   |
| 0.1514        | 14.0    | 1687 | 0.0413          | 0.9924   |
| 0.1514        | 14.9959 | 1807 | 0.0344          | 0.9945   |
| 0.1514        | 16.0    | 1928 | 0.0508          | 0.9924   |
| 0.0161        | 16.9959 | 2048 | 0.0436          | 0.9937   |
| 0.0161        | 18.0    | 2169 | 0.0435          | 0.9931   |
| 0.0161        | 18.9959 | 2289 | 0.0428          | 0.9945   |
| 0.0161        | 20.0    | 2410 | 0.0425          | 0.9947   |
| 0.0161        | 20.9959 | 2530 | 0.0432          | 0.9947   |
| 0.0161        | 22.0    | 2651 | 0.0438          | 0.9947   |
| 0.0161        | 22.9959 | 2771 | 0.0437          | 0.9950   |
| 0.0161        | 24.0    | 2892 | 0.0438          | 0.9950   |
| 0.0011        | 24.8963 | 3000 | 0.0438          | 0.9950   |


### Framework versions

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