---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: psst-model-4e-1s-difflib
  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. -->

# psst-model-4e-1s-difflib

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: 0.3447
- Wer: 0.1540
- Iu F1: 0.7087
- Iu Tp: 810
- Iu Fp: 478
- Iu Fn: 188

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use 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: 332
- training_steps: 4740

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Iu F1  | Iu Tp | Iu Fp | Iu Fn |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:-----:|:-----:|:-----:|
| 1.0729        | 0.4998 | 592  | 0.5149          | 0.2641 | 0.6233 | 402   | 312   | 174   |
| 0.9312        | 0.9996 | 1184 | 0.4770          | 0.2695 | 0.7009 | 457   | 271   | 119   |
| 0.5909        | 1.4989 | 1776 | 0.4784          | 0.2608 | 0.7393 | 380   | 72    | 196   |
| 0.5226        | 1.9987 | 2368 | 0.4648          | 0.2585 | 0.7708 | 454   | 148   | 122   |
| 0.2837        | 2.4981 | 2960 | 0.4956          | 0.2201 | 0.7619 | 448   | 152   | 128   |
| 0.2858        | 2.9979 | 3552 | 0.4899          | 0.2193 | 0.7742 | 468   | 165   | 108   |
| 0.1001        | 3.4973 | 4144 | 0.5498          | 0.2149 | 0.7788 | 456   | 139   | 120   |
| 0.0915        | 3.9970 | 4736 | 0.5480          | 0.2154 | 0.7853 | 461   | 137   | 115   |
| 0.0915        | 4.0    | 4740 | 0.5480          | 0.2153 | 0.7853 | 461   | 137   | 115   |


### Framework versions

- Transformers 5.6.2
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.22.2