File size: 4,653 Bytes
5a5a343 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
---
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: 70.3225806451613
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: 0.9647
- Wer: 70.3226
## 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: 16
- eval_batch_size: 16
- 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: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 6.0651 | 0.6897 | 50 | 5.7375 | 162.9032 |
| 4.9066 | 1.3793 | 100 | 5.3309 | 93.5484 |
| 4.2186 | 2.0690 | 150 | 4.7377 | 89.3548 |
| 3.628 | 2.7586 | 200 | 4.0118 | 81.6129 |
| 3.0181 | 3.4483 | 250 | 3.6058 | 81.6129 |
| 2.6682 | 4.1379 | 300 | 3.2728 | 78.3871 |
| 2.3183 | 4.8276 | 350 | 2.8405 | 75.4839 |
| 1.9084 | 5.5172 | 400 | 2.1841 | 71.9355 |
| 1.2191 | 6.2069 | 450 | 1.2534 | 73.5484 |
| 0.8483 | 6.8966 | 500 | 1.1853 | 73.5484 |
| 0.8115 | 7.5862 | 550 | 1.1503 | 70.9677 |
| 0.7512 | 8.2759 | 600 | 1.1072 | 73.5484 |
| 0.7064 | 8.9655 | 650 | 1.0806 | 74.5161 |
| 0.6779 | 9.6552 | 700 | 1.0477 | 75.1613 |
| 0.6345 | 10.3448 | 750 | 1.0352 | 74.8387 |
| 0.6097 | 11.0345 | 800 | 1.0186 | 73.8710 |
| 0.5927 | 11.7241 | 850 | 1.0120 | 74.5161 |
| 0.5619 | 12.4138 | 900 | 1.0017 | 73.5484 |
| 0.5349 | 13.1034 | 950 | 0.9879 | 70.0 |
| 0.5207 | 13.7931 | 1000 | 0.9900 | 70.0 |
| 0.5168 | 14.4828 | 1050 | 0.9828 | 173.8710 |
| 0.4703 | 15.1724 | 1100 | 0.9676 | 73.5484 |
| 0.476 | 15.8621 | 1150 | 0.9729 | 175.8065 |
| 0.4443 | 16.5517 | 1200 | 0.9652 | 74.1935 |
| 0.4215 | 17.2414 | 1250 | 0.9635 | 176.1290 |
| 0.4206 | 17.9310 | 1300 | 0.9631 | 179.3548 |
| 0.3971 | 18.6207 | 1350 | 0.9687 | 70.6452 |
| 0.3838 | 19.3103 | 1400 | 0.9543 | 147.7419 |
| 0.3791 | 20.0 | 1450 | 0.9594 | 68.3871 |
| 0.3441 | 20.6897 | 1500 | 0.9608 | 257.0968 |
| 0.3574 | 21.3793 | 1550 | 0.9589 | 71.2903 |
| 0.3323 | 22.0690 | 1600 | 0.9619 | 69.6774 |
| 0.3187 | 22.7586 | 1650 | 0.9552 | 154.1935 |
| 0.3011 | 23.4483 | 1700 | 0.9568 | 67.0968 |
| 0.2997 | 24.1379 | 1750 | 0.9580 | 70.9677 |
| 0.287 | 24.8276 | 1800 | 0.9566 | 70.6452 |
| 0.2747 | 25.5172 | 1850 | 0.9694 | 68.3871 |
| 0.2665 | 26.2069 | 1900 | 0.9544 | 69.0323 |
| 0.2565 | 26.8966 | 1950 | 0.9518 | 155.8065 |
| 0.2448 | 27.5862 | 2000 | 0.9579 | 68.7097 |
| 0.2377 | 28.2759 | 2050 | 0.9589 | 67.0968 |
| 0.2323 | 28.9655 | 2100 | 0.9590 | 68.7097 |
| 0.2224 | 29.6552 | 2150 | 0.9647 | 70.3226 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.2.0
- Tokenizers 0.20.3 |