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---
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: 171.5307582260372
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: 2.9413
- Wer: 171.5308
## 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: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 6.8678 | 0.0244 | 25 | 4.4434 | 154.2203 |
| 2.6877 | 0.0489 | 50 | 3.4026 | 144.0629 |
| 1.8792 | 0.0733 | 75 | 3.2962 | 77.3963 |
| 1.5587 | 0.0978 | 100 | 3.2969 | 78.9700 |
| 1.4194 | 0.1222 | 125 | 2.9920 | 75.1073 |
| 1.2356 | 0.1467 | 150 | 2.9471 | 184.2632 |
| 1.1741 | 0.1711 | 175 | 2.9542 | 189.4134 |
| 1.0451 | 0.1956 | 200 | 2.9413 | 171.5308 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.2.0
- Datasets 3.1.0
- Tokenizers 0.19.1 |