---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-finetuned2222222222222222222222222222222
  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-finetuned2222222222222222222222222222222

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0018
- Wer: 0.125

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.7056        | 0.8   | 20   | 6.4502          | 16.25  |
| 4.7836        | 1.6   | 40   | 2.9149          | 10.375 |
| 1.8399        | 2.4   | 60   | 0.8254          | 7.875  |
| 0.3132        | 3.2   | 80   | 0.0852          | 3.875  |
| 0.0335        | 4.0   | 100  | 0.0190          | 1.7500 |
| 0.0067        | 4.8   | 120  | 0.0080          | 1.0    |
| 0.0032        | 5.6   | 140  | 0.0050          | 0.375  |
| 0.0021        | 6.4   | 160  | 0.0039          | 0.125  |
| 0.0017        | 7.2   | 180  | 0.0034          | 0.125  |
| 0.0015        | 8.0   | 200  | 0.0030          | 0.125  |
| 0.0013        | 8.8   | 220  | 0.0027          | 0.125  |
| 0.0012        | 9.6   | 240  | 0.0025          | 0.125  |
| 0.0011        | 10.4  | 260  | 0.0023          | 0.125  |
| 0.001         | 11.2  | 280  | 0.0021          | 0.125  |
| 0.0009        | 12.0  | 300  | 0.0020          | 0.125  |
| 0.0009        | 12.8  | 320  | 0.0020          | 0.125  |
| 0.0009        | 13.6  | 340  | 0.0019          | 0.125  |
| 0.0008        | 14.4  | 360  | 0.0018          | 0.125  |
| 0.0009        | 15.2  | 380  | 0.0018          | 0.125  |
| 0.0008        | 16.0  | 400  | 0.0018          | 0.125  |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.2