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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
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