metadata
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: 75.9656652360515
name: Wer
Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the ASR_Synthetic_Speecht5_TTS dataset. It achieves the following results on the evaluation set:
- Loss: 3.1269
- Wer: 75.9657
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: 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: 100
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.8335 | 0.0244 | 25 | 7.0413 | 196.1373 |
| 6.5445 | 0.0489 | 50 | 5.3231 | 160.5150 |
| 4.2166 | 0.0733 | 75 | 3.6955 | 144.6352 |
| 2.2081 | 0.0978 | 100 | 3.5441 | 84.9785 |
| 1.815 | 0.1222 | 125 | 3.4335 | 83.4049 |
| 1.6465 | 0.1467 | 150 | 3.2851 | 136.9099 |
| 1.5241 | 0.1711 | 175 | 3.3021 | 357.3677 |
| 1.3811 | 0.1956 | 200 | 3.2476 | 81.5451 |
| 1.2553 | 0.2200 | 225 | 3.1495 | 132.1888 |
| 1.3158 | 0.2445 | 250 | 3.1816 | 76.9671 |
| 1.2942 | 0.2689 | 275 | 3.1349 | 74.3920 |
| 1.1935 | 0.2934 | 300 | 3.1269 | 75.9657 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.2.0
- Datasets 3.1.0
- Tokenizers 0.19.1