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---
library_name: peft
language:
- it
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- Dysarthria_Synthetic_Easycall_Common
metrics:
- wer
model-index:
- name: Whisper Medium
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Dysarthria_Synthetic_Easycall_Common
type: Dysarthria_Synthetic_Easycall_Common
config: default
split: train
args: default
metrics:
- type: wer
value: 62.58064516129033
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 Dysarthria_Synthetic_Easycall_Common dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8596
- Wer: 62.5806
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 5.3706 | 0.6897 | 50 | 4.0385 | 81.2903 |
| 1.6886 | 1.3793 | 100 | 1.1083 | 72.5806 |
| 0.6572 | 2.0690 | 150 | 0.9583 | 63.2258 |
| 0.4765 | 2.7586 | 200 | 0.9143 | 121.9355 |
| 0.3623 | 3.4483 | 250 | 0.8818 | 118.0645 |
| 0.2794 | 4.1379 | 300 | 0.8554 | 63.2258 |
| 0.2252 | 4.8276 | 350 | 0.8596 | 62.5806 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.2.0
- Tokenizers 0.20.3 |