---
library_name: peft
language:
- it
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- ASR_Synthetic_Speecht5_TTS
metrics:
- wer
model-index:
- name: Whisper Medium
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: ASR_Synthetic_Speecht5_TTS
      type: ASR_Synthetic_Speecht5_TTS
      config: default
      split: test
      args: default
    metrics:
    - type: wer
      value: 141.63090128755366
      name: Wer
---

<!-- 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 Medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the ASR_Synthetic_Speecht5_TTS dataset.
It achieves the following results on the evaluation set:
- Loss: 9.8059
- Wer: 141.6309

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer       |
|:-------------:|:------:|:----:|:---------------:|:---------:|
| 6.891         | 0.0244 | 25   | 4.4284          | 157.0815  |
| 3.4032        | 0.0489 | 50   | 5.4864          | 1025.8941 |
| 6.9892        | 0.0733 | 75   | 11.7361         | 120.7439  |
| 7.1852        | 0.0978 | 100  | 9.8059          | 141.6309  |


### Framework versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.2.0
- Datasets 3.1.0
- Tokenizers 0.19.1