---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-gcf
  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-gcf

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4385
- Wer: 100.1274

## 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: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer       |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 0.9963        | 1.4085  | 200  | 3.4896          | 101.2739  |
| 0.6015        | 2.8169  | 400  | 3.0877          | 1097.9618 |
| 0.3216        | 4.2254  | 600  | 2.8618          | 99.7452   |
| 0.2368        | 5.6338  | 800  | 2.6891          | 100.1274  |
| 0.1739        | 7.0423  | 1000 | 2.5483          | 421.6561  |
| 0.1892        | 8.4507  | 1200 | 2.4829          | 104.5860  |
| 0.1273        | 9.8592  | 1400 | 2.4358          | 1683.6943 |
| 0.1256        | 10.5634 | 1500 | 2.4385          | 100.1274  |


### Framework versions

- Transformers 5.5.0
- Pytorch 2.4.1+cu124
- Datasets 3.6.0
- Tokenizers 0.22.2
